Optimizing risk stratification in heart failure and the selection of candidates for heart transplantation | Revista Portuguesa de Cardiologia (English edition)

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Soares, Ana Luísa Papoila, Iola Pinto, Joana Feliciano, Luís Almeida-Morais, Ana Abreu, Rui Cruz Ferreira" "autores" => array:8 [ 0 => array:4 [ "nombre" => "Tiago" "apellidos" => "Pereira-da-Silva" "email" => array:1 [ 0 => "tiagopsilva@sapo.pt" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "Rui" "apellidos" => "M. Soares" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 2 => array:3 [ "nombre" => "Ana Luísa" "apellidos" => "Papoila" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] 1 => array:2 [ "etiqueta" => "c" "identificador" => "aff0015" ] ] ] 3 => array:3 [ "nombre" => "Iola" "apellidos" => "Pinto" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "d" "identificador" => "aff0020" ] 1 => array:2 [ "etiqueta" => "e" "identificador" => "aff0025" ] ] ] 4 => array:3 [ "nombre" => "Joana" "apellidos" => "Feliciano" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 5 => array:3 [ "nombre" => "Luís" "apellidos" => "Almeida-Morais" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 6 => array:3 [ "nombre" => "Ana" "apellidos" => "Abreu" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 7 => array:3 [ "nombre" => "Rui" "apellidos" => "Cruz Ferreira" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] ] "afiliaciones" => array:5 [ 0 => array:3 [ "entidad" => "Department of Cardiology, Hospital de Santa Marta, Centro Hospitalar de Lisboa Central, Lisbon, Portugal" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Department of Biostatistics and Informatics, NOVA Medical School, Universidade NOVA de Lisboa, Lisbon, Portugal" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Research Unit, Centro Hospitalar de Lisboa Central, Lisbon, Portugal" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Departmental Area of Mathematics, Instituto Superior de Engenharia de Lisboa, Universidade NOVA de Lisboa, Lisbon, Portugal" "etiqueta" => "d" "identificador" => "aff0020" ] 4 => array:3 [ "entidad" => "Center for Mathematics and Applications, Faculty of Sciences and Technology, Universidade NOVA de Lisboa, Lisbon, Portugal" "etiqueta" => "e" "identificador" => "aff0025" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "pt" => array:1 [ "titulo" => "Aprimoramento da estratificação de risco na insuficiência cardíaca e da seleção de candidatos a transplantação cardíaca" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1076 "Ancho" => 2915 "Tamanyo" => 195734 ] ] "descripcion" => array:1 [ "en" => "Event-free survival up to 36 months of follow-up (excluding patients with VE/VCO2 slope ≥39.0) and 95% CI of estimated survival for each subgroup, according to the combination of sodium (136.0 mEq/l), creatinine (1.0 mg/dl) and variation of end-tidal carbon dioxide partial pressure (0.45 kPa) cut-off values. Group 1: up to one abnormal parameter; group 2: two abnormal parameters; group 3: three abnormal parameters. CI: 95% confidence interval; ISHLT: International Society for Heart and Lung Transplantation; VCO2: carbon dioxide production; VE: minute ventilation." ] ] ] "textoCompleto" => "IntroductionA wide variety of predictors of adverse outcome in heart failure (HF) have been described and it can be difficult to choose the most appropriate tools in clinical practice.<a class="elsevierStyleCrossRefs" href="#bib0110">1,2</a> Risk stratification should be as accurate as possible, particularly when selecting patients for heart transplantation (HTX), as procedure-related morbidity and mortality are non-negligible and it cannot be offered to all candidates due to the shortage of donors.<a class="elsevierStyleCrossRef" href="#bib0120">3</a> For ambulatory patients, both the American Heart Association and the International Society for Heart and Lung Transplantation (ISHLT) recommend the use of peak oxygen consumption (VO2 max) achieved in cardiopulmonary exercise testing (CPET), with optional use of risk scores in gray zones; VO2 max <10-12 ml/kg/min is considered a listing criterion for HTX.<a class="elsevierStyleCrossRefs" href="#bib0125">4,5</a> We believe that risk stratification and referral criteria for HTX can be improved using simple parameters. Additional CPET variables have shown to be accurate for risk stratification, particularly the ventilatory efficiency (VE/VCO2) slope.<a class="elsevierStyleCrossRefs" href="#bib0135">6–8</a> However, most studies that highlight the value of ergospirometric parameters have focused mainly on clinical and CPET data, without comprehensive assessment of other parameters, and few had long-term follow-up.<a class="elsevierStyleCrossRefs" href="#bib0135">6–9</a> Identifying robust criteria for selecting patients for HTX should be based on a comprehensive prospective clinical and complementary assessment.Our aims were to identify the most accurate predictors of adverse events in non-transplanted patients with HF and an approach to optimize the selection of patients for HTX.MethodsThe investigation conforms to the principles outlined in the Declaration of Helsinki. The institutional ethics committee approved the study protocol.Patient selection and complementary assessmentThis single-center analysis included all patients with HF with left ventricular ejection fraction (LVEF) ≤40%, in New York Heart Association class II or III, followed in the heart failure clinic of our institution between 2000 and 2009. All patients referred to the heart failure clinic underwent a comprehensive complementary assessment. Clinical, laboratory, electrocardiographic, echocardiographic, and CPET data were prospectively collected; all these exams were performed within a period of one month in each patient.Patients aged <18 years and those with planned percutaneous coronary revascularization or cardiac surgery, exercise-limiting comorbidities (cerebrovascular disease, musculoskeletal impairment, or severe peripheral vascular disease), previous HTX, or failure to achieve the anaerobic threshold were excluded.Cardiopulmonary exercise testingMaximal symptom-limited treadmill CPET was performed using the modified Bruce protocol (GE Marquette Series 2000 treadmill). Gas analysis was preceded by calibration of the equipment. Minute ventilation, oxygen uptake and carbon dioxide production were acquired breath-by-breath, using a SensorMedics Vmax 229 gas analyzer. Patients were encouraged to exercise until the respiratory exchange ratio (ratio between carbon dioxide production and oxygen consumption) was ≥1.10. VO2 max was defined as the highest 30-s average achieved during exercise and was normalized for body mass, corrected for fat-free mass in obese patients (body mass index >30 kg/m2). The ventilatory threshold was determined by combining the standard methods (V-slope and ventilatory equivalents).<a class="elsevierStyleCrossRef" href="#bib0155">10</a> The VE/VCO2 slope was calculated by least squares linear regression, using data acquired throughout the exercise session.<a class="elsevierStyleCrossRef" href="#bib0155">10</a> Several composite CPET parameters were also calculated.Follow-up and endpointAll patients were followed for 60 months from the date of completion of the above-mentioned complementary exams. Patients were assessed for the occurrence of death, HTX or the need for mechanical circulatory support. Data were obtained from outpatient clinic visits and review of medical charts, and were complemented by a standardized telephone interview with all patients at 12, 36 and 60 months of follow-up.The combined endpoint of cardiac death, urgent HTX (occurring during an unplanned hospitalization for worsening of HF, requiring inotropes) or the need for mechanical circulatory support was analyzed.Statistical analysisCategorical data are presented as frequencies (percentages) and continuous variables as mean (standard deviation) or median (25th-75th percentile), as appropriate. Continuous variables were analyzed using the Student's t test, or the Mann-Whitney test when normality was not verified by the Kolmogorov-Smirnov test; categorical variables were analyzed using the chi-squared or Fisher's exact tests.Univariate and multivariate Cox regression models were applied to time until the combined endpoint, considering the follow-up times of 12, 36 and 60 months. A complete list of the tested variables and a detailed description of the univariate and multivariate analysis are presented as supplementary material (<a class="elsevierStyleCrossRef" href="#sec0065">Supplementary Tables 1 and 2</a>).The 36-month follow-up period was analyzed to identify a possible approach for selecting patients for HTX.<a class="elsevierStyleCrossRefs" href="#bib0140">7,8,11</a> To identify the most accurate individual predictor from the multivariate model, the variable with the highest area under the curve (AUC) on receiver operating characteristic (ROC) analysis (VE/VCO2 slope, post hoc) was selected. To assess the additive value of other predictors to VE/VCO2 slope, the AUC of VE/VCO2 slope was compared with the AUC of the model including all predictors of adverse outcome. The DeLong test was used to compare two correlated ROC curves. In addition, continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI) measures for censored data were calculated.<a class="elsevierStyleCrossRef" href="#bib0165">12</a>The best cut-off value of VE/VCO2 slope for identifying high-risk patients was calculated using the martingale residuals. Since HTX can only be offered to a small subgroup of HF patients, we identified another cut-off value that minimized the rate of misclassified high-risk patients, even if sensitivity decreased to reasonable levels.<a class="elsevierStyleCrossRef" href="#bib0120">3</a> We thus identified a VE/VCO2 slope threshold that provided a high specificity (at least 90%) with at least 50% sensitivity, using the inverse probability of censoring weighting approach.<a class="elsevierStyleCrossRef" href="#bib0170">13</a> Subgroups of high- and low-risk patients were created accordingly. Event-free survival rates of both subgroups were estimated using the Kaplan-Meier method and compared using the log-rank test. To assess whether the identified VE/VCO2 slope threshold is suitable as a potential indication for HTX, two analyses were carried out. Firstly, survival rates of high- and low-risk subgroups of our cohort were compared with survival rates after HTX reported by the ISHLT transplant registry (quarterly data report on survival rates for orthotopic HTX performed in Europe between October 1, 2011 and September 30, 2015), using a previously reported method.<a class="elsevierStyleCrossRefs" href="#bib0150">9,14</a> Since the ISHLT reports overall survival, we studied (for this analysis only) time to death from any cause, right censoring in the event of urgent or non-urgent HTX.<a class="elsevierStyleCrossRef" href="#bib0175">15</a> If the 95% confidence intervals (CI) of estimated survival 36 months after HTX reported by the ISHLT did not overlap with those of high- and low-risk subgroups of our cohort, based on the VE/VCO2 slope threshold, this can be taken as evidence of significant difference.<a class="elsevierStyleCrossRefs" href="#bib0140">7,15</a> Secondly, the NRI and IDI were used to compare discretized VE/VCO2 slope and VO2 max, considering the combined endpoint for the analysis.To further stratify prognosis in low-risk patients, high-risk patients were excluded from subsequent analysis and univariate and multivariate Cox regression models were fitted to the low-risk subgroup. Martingale residuals were used to identify cut-off values for the variables that remained in the model and subgroups of high- and low-risk patients were created accordingly. Event-free survival rates of the subgroups were estimated using the Kaplan-Meier method and compared using the Gehan-Breslow-Wilcoxon test.The level of significance considered was α=0.05. Data were analyzed using SPSS for Windows, version 20.0 (IBM SPSS Inc., Chicago, IL) and the statistical program R Development Core Team (2014), R: A language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, Austria).ResultsA total of 263 patients were included. The combined endpoint occurred in 54 patients (20.5%) within 36 months and in 69 (26.2%) within 60 months. The main baseline data are presented in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>, in which patients with and without events up to 36 months of follow-up are compared and the most important risk predictors identified in univariate Cox regression are presented. Complete data on baseline characteristics and univariate Cox regression are presented in <a class="elsevierStyleCrossRef" href="#sec0065">Supplementary Tables 1 and 2</a>, respectively.<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>Cumulative adverse events occurring in different follow-up periods are presented in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>. The independent predictors of adverse events identified in multivariate Cox regression with follow-up times of 12, 36 and 60 months are presented in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>. At 36 months of follow-up, VE/VCO2 slope, creatinine levels and LVEF were independent predictors of adverse events. The VE/VCO2 slope had the highest Wald chi-square value in univariate and multivariate analysis at 36 months and was the parameter with the highest AUC in all multivariate models, considering 12, 36 and 60 months of follow-up. Specifically for the 36-month follow-up period, the AUC of the overall model including all predictors of adverse outcome did not differ significantly from the AUC of the model with VE/VCO2 slope alone (DeLong test p=0.103). In addition, the overall NRI was 63.4% (95% CI 33.5-93.4%) and the IDI was 0.019 (95% CI [-0.01]-[0.046]), when creatinine levels and LVEF were added to VE/VCO2 slope; as the 95% CI of IDI includes the null value, the improvement in model performance is negligible. Since the other predictors included in the model (creatinine levels and LVEF) did not add significantly to VE/VCO2 slope for risk prediction, only VE/VCO2 slope was selected to obtain a cut-off value for clinical use.<elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0015"></elsevierMultimedia>Based on the martingale residuals, the best estimated cut-off value for VE/VCO2 slope to identify patients at higher risk at 36 months of follow-up was 32.0 (specificity 80%, sensitivity 83%) (<a class="elsevierStyleCrossRef" href="#sec0065">Supplementary Figure 1</a>). However, a threshold of 39.0 provided higher specificity (97%), with 52% sensitivity. The estimated 36-month survival for high-risk (VE/VCO2 slope ≥39.0) and low-risk (VE/VCO2 slope <39.0) patients was significantly different (<a class="elsevierStyleCrossRef" href="#fig0005">Figure 1</a>).<elsevierMultimedia ident="fig0005"></elsevierMultimedia>A threshold of 39.0 for VE/VCO2 slope was assessed as a potential listing criterion for HTX. Firstly, the 95% CIs of estimated survival (considering all-cause death) for high- and low-risk subgroups did not overlap with those of post-HTX reported by the ISHLT.<a class="elsevierStyleCrossRef" href="#bib0175">15</a> Secondly, the VE/VCO2 slope had a higher AUC than VO2 max, considering both as continuous variables (AUC of VO2 max 0.79, 95% CI 0.72-0.87; DeLong test for comparison p=0.009). Moreover, there was a significant improvement in the percentage of correct classification using the VE/VCO2 slope threshold of 39.0, in comparison to discretized VO2 max (<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>): considering the VO2 max threshold of 10.0 ml/kg/min, the overall NRI and IDI were 82.2% (95% CI 52.3-112.1%) and 0.278 (95% CI 0.182-0.373), respectively; considering the VO2 max threshold of 12.0 ml/kg/min, the overall NRI and IDI were 93.3% (95% CI 63.4-123.2%) and 0.226 (95% CI 0.141-0.311), respectively. Since the data consistently favored the use of VE/VCO2 slope as an indication for HTX, high-risk patients (VE/VCO2 slope ≥39.0) were excluded from subsequent analysis. In the other 229 patients, 27 (11.8%) events occurred during 36 months of follow-up. Sodium and creatinine levels, LVEF, and variation achieved in CPET (anaerobic threshold minus baseline) of the end-tidal carbon dioxide partial pressure (Δ PetCO2) were independent predictors of adverse events at 36 months of follow-up (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). The AUC was similar for these predictors. For LVEF, the flatness of the martingale residuals smoother did not enable a suitable cut-off point to be identified that discriminated high- and low-risk patients (<a class="elsevierStyleCrossRef" href="#sec0065">Supplementary Figure 2</a>); sodium ≤136.0 mEq/l, creatinine ≥1.0 mg/dl and Δ PetCO2 ≤0.45 kPa (3.4 mmHg) were associated with higher risk of adverse events (specificity 63%, 61% and 63%, sensitivity 77%, 74% and 74%, respectively). Eight subgroups were created according to the three mentioned cut-off values (<a class="elsevierStyleCrossRef" href="#sec0065">Supplementary Figure 3</a>). Prognosis was similar for patients with up to one variable (sodium, creatinine or Δ PetCO2) with abnormal values (classified according to the thresholds identified); prognosis was similar for patients with two variables with abnormal values, and event-free survival was worst when the three variables were classified as abnormal. Three groups were created accordingly (<a class="elsevierStyleCrossRef" href="#fig0010">Figure 2</a>); prognosis was significantly different for the three categories.<elsevierMultimedia ident="tbl0020"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia>DiscussionThe most accurate predictor of adverse outcome in patients with HF with reduced LVEF was VE/VCO2 slope and the best threshold for identifying patients who may benefit from HTX was 39.0. Sodium levels, creatinine levels and Δ PetCO2 were able to identify low-risk patients with excellent outcome.Risk stratification in HF and selecting patients for HTX are challenging. Mancini et al.<a class="elsevierStyleCrossRef" href="#bib0190">18</a> showed in an ancillary study that VO2 max is a valuable parameter for selecting patients for HTX, and subsequently refined their cut-off values.<a class="elsevierStyleCrossRefs" href="#bib0160">11,19</a> Currently, the American Heart Association recommends listing ambulatory patients for HTX when VO2 max is <10 ml/kg/min with achievement of anaerobic metabolism, and to defer when VO2 max is >14 ml/kg/min.<a class="elsevierStyleCrossRef" href="#bib0125">4</a> Mancini et al.<a class="elsevierStyleCrossRef" href="#bib0195">19</a> proposed a similar decision algorithm, also recommending assessment using the Heart Failure Survival Score (HFSS). The ISHLT recommends listing when VO2 max is <12 ml/kg/min on beta-blockers, deferring when it is >14 ml/kg/min, and using the HFSS in the gray zone.<a class="elsevierStyleCrossRef" href="#bib0130">5</a> Only in the presence of a submaximal CPET should VE/VCO2 slope be considered as a listing criterion, according to the ISHLT guidelines.<a class="elsevierStyleCrossRef" href="#bib0130">5</a> Risk stratification and patient selection for HTX could probably be improved.<a class="elsevierStyleCrossRef" href="#bib0140">7</a> However, the use of randomized controlled trials to address the issue of listing criteria is hindered by ethical and social considerations. In this context, data from robust registries on non-transplanted HF patients receiving contemporary pharmacological and device therapy are of great value.We evaluated an extensive range of clinical, laboratory, electrocardiographic, echocardiographic, and CPET parameters as potential predictors of adverse outcome. The single best parameter of all those studied was VE/VCO2 slope, yielding the highest Wald chi-square value and the highest AUC at 12, 36 and 60 months of follow-up, and with even more discriminative power than the HFSS, which combines different variables. Of note, VO2 max did not remain in any multivariate model in our cohort. The 60-month follow-up period was not used to identify an approach for selecting patients for HTX, since prognostic reassessment should be undertaken earlier.<a class="elsevierStyleCrossRefs" href="#bib0140">7,8</a> Nevertheless, the long-term follow-up carried out confirmed the consistently higher accuracy of VE/VCO2 slope over a long period, in comparison to other parameters. This finding has not been properly addressed in previous studies.<a class="elsevierStyleCrossRefs" href="#bib0135">6–8</a> Arena et al.<a class="elsevierStyleCrossRef" href="#bib0135">6</a> showed that the risk of adverse events increases continuously over different categories of VE/VCO2 slope. However, thresholds are useful for clinical practice, and VE/VCO2 slope values of 34.0 and 35.0 have been proposed as optimal criteria for classifying patients with HF as high- and low-risk.<a class="elsevierStyleCrossRefs" href="#bib0130">5,14</a> In line with these thresholds, the risk of adverse events began to rise for values above 32.0 in our cohort, as shown by analysis of the martingale residuals. Although the specificity for this threshold was not low (80%), a non-negligible proportion of patients would be classified as high-risk even though they would not experience an adverse outcome. If this was considered a listing criterion for HTX, issues related to the shortage of donors and to the morbidity and mortality following HTX might arise, by listing patients who were at a less severe stage of HF. Therefore, the threshold of 39.0, which provides very high specificity with reasonable sensitivity, may be more appropriate for selecting patients for HTX than lower cut-off values.<a class="elsevierStyleCrossRefs" href="#bib0130">5,14</a> Freedom from the combined endpoint at 36 months of follow-up was very low (19.3%) for patients with VE/VCO2 slope ≥39.0. Even though this threshold was not primarily identified to predict total mortality, the 95% CI of estimated overall survival of high- and low-risk subgroups did not overlap with those of post-HTX reported by the ISHLT.<a class="elsevierStyleCrossRef" href="#bib0175">15</a> This finding suggests that, for our cohort, survival of hypothetically transplanted patients would be better than survival of non-transplanted high-risk patients and worse than survival of non-transplanted low-risk patients. In addition, the threshold of 39.0 for VE/VCO2 slope was more accurate than the cut-off values of 10 or 12 ml/kg/min for VO2 max, which are recommended as listing criteria.<a class="elsevierStyleCrossRefs" href="#bib0125">4,5</a> VE/VCO2 slope has previously been reported as providing a discriminative power at least as good as VO2 max for predicting adverse events.<a class="elsevierStyleCrossRefs" href="#bib0135">6,9</a> Nevertheless, the majority of studies that highlighted the value of VE/VCO2 slope did not assess this parameter in the light of a comprehensive assessment of clinical, laboratory, electrocardiographic, echocardiographic and CPET parameters, and few had a long-term follow-up.<a class="elsevierStyleCrossRefs" href="#bib0135">6–8</a> Compared to previous studies, we carried out a more comprehensive (and prospective) baseline assessment, with a long-term follow-up, and employing a robust statistical analysis with consistent results. Based on our results, patients with VE/VCO2 slope ≥39.0 may benefit from HTX.For low-risk non-transplanted patients with sodium levels >136.0 mEq/l, creatinine levels <1.0 mg/dl and Δ PetCO2 >0.45 kPa (3.4 mmHg), or patients with up to one of these variables classified as abnormal, the prognosis was excellent and total mortality was lower than that reported for post-HTX.<a class="elsevierStyleCrossRef" href="#bib0175">15</a> Sodium and creatinine levels are known independent predictors of adverse events in HF and are included in risk scores such as the HFSS and the Meta-Analysis Global Group in Chronic Heart Failure score.<a class="elsevierStyleCrossRefs" href="#bib0110">1,2</a> PetCO2 at rest and at the anaerobic threshold were shown to stratify risk beyond the VE/VCO2 slope, and combining them into a single parameter (Δ PetCO2) may be more practical and accurate.<a class="elsevierStyleCrossRefs" href="#bib0205">20,21</a> We suggest that particular attention should be paid to sodium levels, creatinine levels and Δ PetCO2, in addition to VE/VCO2 slope, particularly for identifying low-risk patients in clinical practice.Some limitations of the study should be acknowledged. Firstly, the analyzed cohort was not large. However, it was possible to identify the most important independent predictors of adverse outcome in HF and a strategy for optimizing the selection of patients for HTX, and the results were consistent using different statistical analyses. The sample size is similar to those of other studies that highlighted the value of CPET parameters, including for the selection of patients for HTX.<a class="elsevierStyleCrossRefs" href="#bib0135">6,14,18,20,21</a> Secondly, this was a single-center study. Nevertheless, this meant that the CPET protocol was consistent in all cases, and may have reduced the number of physicians responsible for the interpretation of the exam, reducing interobserver variability. Thirdly, listing for HTX is a complex and multidisciplinary decision and should not rely solely on ‘magic numbers’ of specific parameters from complementary exams; however, thresholds are useful in clinical practice, as pointed out above. In addition, the aim was not to replace but to potentially optimize current listing criteria for HTX. The decision threshold we propose is in line with current practice in different centers, where clinical decisions are supported by VE/VCO2 slope data in addition to VO2 max, even though current guidelines do not address this approach.<a class="elsevierStyleCrossRefs" href="#bib0125">4,5,7</a> A further validation study would certainly be useful.ConclusionsAmong a large variety of predictors of adverse outcome in ambulatory patients with HF with reduced LVEF, the most accurate was VE/VCO2 slope. Patients with VE/VCO2 slope of 39.0 or higher may benefit from HTX. Beyond the VE/VCO2 slope, sodium levels, creatinine levels and Δ PetCO2 were able to identify patients with excellent outcome.FundingNone.Conflicts of interestThe authors have no conflicts of interest to declare." "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres1005649" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction and Aims" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec965438" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1005650" "titulo" => "Resumo" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Introdução e objetivos" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusões" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec965437" "titulo" => "Palavras-chave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Methods" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Patient selection and complementary assessment" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Cardiopulmonary exercise testing" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Follow-up and endpoint" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Statistical analysis" ] ] ] 6 => array:2 [ "identificador" => "sec0035" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0040" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0045" "titulo" => "Conclusions" ] 9 => array:2 [ "identificador" => "sec0050" "titulo" => "Funding" ] 10 => array:2 [ "identificador" => "sec0055" "titulo" => "Conflicts of interest" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2017-01-22" "fechaAceptado" => "2017-06-18" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec965438" "palabras" => array:6 [ 0 => "Cardiopulmonary exercise testing" 1 => "Heart failure" 2 => "Heart transplantation" 3 => "Peak oxygen consumption" 4 => "Risk stratification" 5 => "Ventilatory efficiency slope" ] ] ] "pt" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palavras-chave" "identificador" => "xpalclavsec965437" "palabras" => array:6 [ 0 => "Prova de esforço cardiorrespiratória" 1 => "Insuficiência cardíaca" 2 => "Transplantação cardíaca" 3 => "Consumo de oxigénio de pico" 4 => "Estratificação de risco" 5 => "Declive da eficiência ventilatória" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "Introduction and AimsSelecting patients for heart transplantation is challenging. We aimed to identify the most important risk predictors in heart failure and an approach to optimize the selection of candidates for heart transplantation. MethodsAmbulatory patients followed in our center with symptomatic heart failure and left ventricular ejection fraction ≤40% prospectively underwent a comprehensive baseline assessment including clinical, laboratory, electrocardiographic, echocardiographic, and cardiopulmonary exercise testing parameters. All patients were followed for 60 months. The combined endpoint was cardiac death, urgent heart transplantation or need for mechanical circulatory support, up to 36 months. ResultsIn the 263 enrolled patients (75% male, age 54±12 years), 54 events occurred. The independent predictors of adverse outcome were ventilatory efficiency (VE/VCO2) slope (HR 1.14, 95% CI 1.11-1.18), creatinine level (HR 2.23, 95% CI 1.14-4.36), and left ventricular ejection fraction (HR 0.96, 95% CI 0.93-0.99). VE/VCO2 slope was the most accurate risk predictor at any follow-up time analyzed (up to 60 months). The threshold of 39.0 yielded high specificity (97%), discriminated a worse or better prognosis than that reported for post-heart transplantation, and outperformed peak oxygen consumption thresholds of 10.0 or 12.0 ml/kg/min. For low-risk patients (VE/VCO2 slope <39.0), sodium and creatinine levels and variations in end-tidal carbon dioxide partial pressure on exercise identified those with excellent prognosis. ConclusionsVE/VCO2 slope was the most accurate parameter for risk stratification in patients with heart failure and reduced ejection fraction. Those with VE/VCO2 slope ≥39.0 may benefit from heart transplantation." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction and Aims" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] "pt" => array:3 [ "titulo" => "Resumo" "resumen" => "Introdução e objetivosA seleção de doentes para transplantação cardíaca é difícil. Procurámos identificar os preditores de risco mais relevantes na insuficiência cardíaca e uma abordagem para aprimorar a seleção de candidatos a transplantação. MétodosDoentes sintomáticos com insuficiência cardíaca e fração de ejeção ventricular esquerda ≤ 40%, ambulatórios, seguidos no nosso centro, completaram prospetivamente uma avaliação basal abrangente, inclusive parâmetros clínicos, laboratoriais, eletrocardiográficos, ecocardiográficos e prova de esforço cardiorrespiratória; foram seguidos por 60 meses. Endpoint combinado: morte de causa cardíaca, transplantação urgente ou necessidade de assistência mecânica, até aos 36 meses. ResultadosNos 263 doentes incluídos (75% homens, 54 ±12 anos) ocorreram 54 eventos. O declive da eficiência ventilatória (declive VE/VCO2) (HR 1,14, IC 95% 1,11-1,18), a creatinina (HR 2,23, IC 95% 1,14-4,36) e a fração de ejeção ventricular esquerda (HR 0,96, IC 95% 0,93-0,99) foram preditores independentes de eventos. O declive VE/VCO2 foi o melhor preditor em qualquer período analisado (até aos 60 meses). O limiar 39,0 apresentou elevada especificidade (97%), discriminou um prognóstico melhor ou pior do que o reportado no pós-transplante cardíaco e superou os limiares 10,0 ou 12,0 mL/kg/min de consumo de oxigénio de pico. Em doentes de baixo risco (declive VE/VCO2 <39,0) o sódio, a creatinina e a variação no exercício da pressão parcial de dióxido de carbono expirado identificaram aqueles com excelente pronóstico. ConclusõesO declive VE/VCO2 foi o melhor preditor de risco em doentes com insuficiência cardíaca e fração de ejeção reduzida. Doentes com declive VE/VCO2 ≥39,0 poderão beneficiar de transplantação cardíaca." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Introdução e objetivos" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusões" ] ] ] ] "apendice" => array:1 [ 0 => array:1 [ "seccion" => array:1 [ 0 => array:4 [ "apendice" => "<elsevierMultimedia ident="upi0005"></elsevierMultimedia><elsevierMultimedia ident="upi0010"></elsevierMultimedia>" "etiqueta" => "Appendix A" "titulo" => "Supplementary material" "identificador" => "sec0065" ] ] ] ] "nomenclatura" => array:1 [ 0 => array:3 [ "identificador" => "nom0005" "titulo" => "List of abbreviations" "listaDefinicion" => array:1 [ 0 => array:1 [ "definicion" => array:11 [ 0 => array:2 [ "termino" => "Δ PetCO2" "descripcion" => "variation of end-tidal carbon dioxide partial pressure" ] 1 => array:2 [ "termino" => "CI" "descripcion" => "confidence interval" ] 2 => array:2 [ "termino" => "CPET" "descripcion" => "cardiopulmonary exercise testing" ] 3 => array:2 [ "termino" => "HF" "descripcion" => "heart failure" ] 4 => array:2 [ "termino" => "HTX" "descripcion" => "heart transplantation" ] 5 => array:2 [ "termino" => "IDI" "descripcion" => "integrated discrimination improvement" ] 6 => array:2 [ "termino" => "ISHLT" "descripcion" => "International Society for Heart and Lung Transplantation" ] 7 => array:2 [ "termino" => "LVEF" "descripcion" => "left ventricular ejection fraction" ] 8 => array:2 [ "termino" => "NRI" "descripcion" => "net reclassification improvement" ] 9 => array:2 [ "termino" => "VO2 max" "descripcion" => "peak oxygen consumption" ] 10 => array:2 [ "termino" => "VE/VCO2 slope" "descripcion" => "ventilatory efficiency slope" ] ] ] ] ] ] "multimedia" => array:8 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1082 "Ancho" => 2919 "Tamanyo" => 202567 ] ] "descripcion" => array:1 [ "en" => "Event-free survival up to 36 months of follow-up according to VE/VCO2 slope threshold of 39.0, and 95% CI of estimated survival for each subgroup. CI: 95% confidence interval; ISHLT: International Society for Heart and Lung Transplantation; VCO2: carbon dioxide production; VE: minute ventilation." ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1076 "Ancho" => 2915 "Tamanyo" => 195734 ] ] "descripcion" => array:1 [ "en" => "Event-free survival up to 36 months of follow-up (excluding patients with VE/VCO2 slope ≥39.0) and 95% CI of estimated survival for each subgroup, according to the combination of sodium (136.0 mEq/l), creatinine (1.0 mg/dl) and variation of end-tidal carbon dioxide partial pressure (0.45 kPa) cut-off values. Group 1: up to one abnormal parameter; group 2: two abnormal parameters; group 3: three abnormal parameters. CI: 95% confidence interval; ISHLT: International Society for Heart and Lung Transplantation; VCO2: carbon dioxide production; VE: minute ventilation." ] ] 2 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Variable \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">All patients \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Events<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">No events<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Chi-square \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Hazard ratio, 95% CI \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " colspan="8" align="left" valign="top">Clinical and electrocardiographic data</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Age (years)<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">54 (12) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">54 (12) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">53 (12) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.718 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.00, 0.98-1.02 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.781 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Male<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">197 (75) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">44 (81) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">153 (73) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.141 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.61, 0.33-1.15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.125 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Diabetes<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">54 (21) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8 (15) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">46 (22) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.248 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.12, 0.60-2.08 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.728 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Ischemic etiology<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">97 (37) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">28 (52) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">69 (33) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.009 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.06, 1.13-3.75 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.018 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">NYHA II (vs. III)<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">200 (76) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">28 (52) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">172 (82) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.22, 0.12-0.42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Sinus rhythm<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">214 (81) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">36 (67) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">178 (85) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.003 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.52, 1.28-4.96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.008 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Loop diuretic<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">234 (89) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">54 (100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">180 (86) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.002 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">24.9, 1.1-546.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.041 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">ACEi/ARB<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">255 (97) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">54 (100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">201 (96) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.309 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.05, 0.01-12.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.285 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Betablocker<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">233 (89) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">48 (89) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">185 (89) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.999 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.41, 0.81-2.43 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.224 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Aldosterone receptor blocker<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">176 (67) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">43 (80) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">133 (64) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.035 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.00, 1.12-3.54 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.018 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Baseline CRT<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">72 (27) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14 (26) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">58 (28) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.342 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.72, 0.64-3.36 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.462 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Baseline ICD<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">85 (32) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">18 (33) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">67 (32) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.117 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.41, 0.79-2.64 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.236 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="8" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="8" align="left" valign="top">Laboratory data</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Creatinine (mg/dl)<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.1 (0.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.2 (0.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.1 (0.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.93, 1.66-9.26 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Sodium (mEq/l)<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">137 (3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">134 (4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">137 (3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">62.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.73, 0.66-0.81 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">NT-proBNP (pg/ml)<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2304 (2821) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4269 (4724) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1898 (2029) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">38.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.01, 1.00-1.01 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Elevated troponin T<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37 (14) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13 (24) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">24 (11) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.004 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.54, 1.54-8.12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.003 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="8" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="8" align="left" valign="top">Echocardiographic data</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">LVEDD (mm/m2)<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">39 (6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42 (7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">39 (5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.006 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.16, 0.04-0.64 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.010 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">LVEF (%)<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">28 (7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23 (6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">28 (8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.92, 0.90-0.95 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">MR<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42 (16) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9 (17) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33 (16) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.988 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.92, 0.30-1.55 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.872 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">RVSD<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42 (16) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">19 (35) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23 (11) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7.09, 3.28-15.33 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="8" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="8" align="left" valign="top">Cardiopulmonary exercise testing data</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">HR recovery (1st minute) (min)<a class="elsevierStyleCrossRef" href="#tblfn0020">d</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">18 (13-29) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13 (8-18) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">19 (15-30) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.90, 0.85-0.93 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Δ double product (mmHg/min)<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11911 (5374) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8564 (4443) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12619 (5547) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.00, 1.00-1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Peak RER<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.10 (0.10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.13 (0.10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.09 (0.09) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.008 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">45.75, 2.59-808.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.011 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">VO2 max (ml/kg/min)e,<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">20.0 (5.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15.6 (4.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">21.1 (5.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">56.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.78, 0.71-0.85 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">VO2 max (% predicted)e,<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">67 (15) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">51 (14) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">71 (16) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">69.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.91, 0.81-0.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Circulatory power (mmHg/ml/kg/min)<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3115 (1123) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2185 (895) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3289 (1132) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">48.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.99, 0.99-0.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Peak oxygen pulse (% predicted)<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">91 (30) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">74 (23) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">95 (30) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">28.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.97, 0.96-0.98 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">OUES<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.8 (0.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.4 (0.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.9 (0.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">49.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.11, 0.05-0.27 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">AT-VO2 (ml/kg/min)<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">16.1 (4.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.6 (3.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.0 (4.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">61.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.74, 0.66-0.81 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">VE/VCO2 slopef,<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">31 (7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40 (9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">29 (5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">139 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.27, 1.19-1.35 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Peak VE/VCO2f,<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">35 (8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42 (10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33 (7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">76.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.14, 1.09-1.19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">AT VE/VCO2f,<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33 (7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40 (9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">31 (6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">78.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.17, 1.08-1.23 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">VE/VCO2 slope/VO2 max (ml/kg/min)-1<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.7 (0.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.9 (1.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.5 (0.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">130 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">5.00, 3.12-8.31 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Baseline PetCO2 (kPa)<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.4 (0.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.2 (0.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.4 (0.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.017 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.21 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.52, 0.30-0.89 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.018 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">AT PetCO2 (kPa)g,<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.9 (0.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.3 (0.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.0 (0.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">49.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.27, 0.17-0.44 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Δ PetCO2 (kPa)g,<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.5 (0.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.1 (0.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.6 (0.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">84.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.03, 0.01-0.17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="8" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="8" align="left" valign="top">Score</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">HFSS<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.7 (1.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7.9 (0.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.8 (0.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">51.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.33, 0.22-0.49 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1702751.png" ] ] ] "notaPie" => array:4 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "Cardiac death, urgent heart transplantation or mechanical circulatory support up to 36 months of follow-up (n=54)." ] 1 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "b" "nota" => "Values expressed as mean (standard deviation)." ] 2 => array:3 [ "identificador" => "tblfn0015" "etiqueta" => "c" "nota" => "Values expressed as n (%)." ] 3 => array:3 [ "identificador" => "tblfn0020" "etiqueta" => "d" "nota" => "Values expressed as median (25th-75th percentile). e,f,gOf these, only VO2 max, VE/VCO2 slope (entire exercise) and Δ PetCO2 were entered in the multivariate model, to avoid multicollinearity. Δ double product: product of peak minus baseline heart rate and systolic blood pressure; Δ PetCO2: anaerobic threshold minus baseline end-tidal carbon dioxide partial pressure; ACEi: angiotensin-converting enzyme inhibitor; ARB: angiotensin receptor blocker; AT: anaerobic threshold; Chi-square: Wald chi-square value; CI: confidence interval; Circulatory power: product of peak oxygen consumption and systolic blood pressure; CRT: cardiac resynchronization therapy, with or without defibrillator; HFSS: Heart Failure Survival Score; HR: heart rate; HR recovery (1st minute): peak heart rate minus heart rate at first minute of recovery; ICD: implantable cardioverter-defibrillator; LVEDD: left ventricular end-diastolic diameter; LVEF: left ventricular ejection fraction; MR: moderate or severe mitral regurgitation; NT-proBNP: N-terminal pro-B-type natriuretic peptide; NYHA: New York Heart Association; OUES: oxygen uptake efficiency slope<a class="elsevierStyleCrossRef" href="#bib0180">16</a>; peak oxygen pulse: peak oxygen consumption/heart rate ratio; PetCO2: end-tidal carbon dioxide partial pressure; RER: respiratory exchange ratio (ratio between carbon dioxide production and oxygen consumption); RVSD: right ventricular systolic dysfunction; VO2 max: peak oxygen consumption; VO2 max (% predicted): based on Wasserman and Hansen's formula; VCO2: carbon dioxide production; VE: minute ventilation; VO2: oxygen consumption." ] ] ] "descripcion" => array:1 [ "en" => "Baseline data and univariate Cox regression analysis for predicting adverse events up to 36 months of follow-up." ] ] 3 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">12 months</th><th class="td" title="table-head " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">36 months</th><th class="td" title="table-head " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">60 months</th></tr><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">n \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">(%) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">n \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">(%) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">n \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">(%) \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Combined endpoint<a class="elsevierStyleCrossRef" href="#tblfn0025">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">54 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">20.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">69 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Death \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">47 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">66 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Cardiac death \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">36 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">49 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">18.6 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Sudden death \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.8 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Worsening of heart failure \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">31 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.8 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Heart transplantation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.4 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Urgent heart transplantation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.5 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Mechanical circulatory support<a class="elsevierStyleCrossRef" href="#tblfn0030">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.1 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1702752.png" ] ] ] "notaPie" => array:2 [ 0 => array:3 [ "identificador" => "tblfn0025" "etiqueta" => "a" "nota" => "Cardiac death, urgent heart transplantation or mechanical circulatory support." ] 1 => array:3 [ "identificador" => "tblfn0030" "etiqueta" => "b" "nota" => "All patients were in Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) profiles 1 or 2.<a class="elsevierStyleCrossRef" href="#bib0185">17</a>" ] ] ] "descripcion" => array:1 [ "en" => "Adverse events at 12, 36 and 60 months of follow-up." ] ] 4 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at3" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Chi-square \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Hazard ratio, 95% CI \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">AUC, 95% CI \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " colspan="5" align="left" valign="top">12-month follow-up<a class="elsevierStyleCrossRef" href="#tblfn0035">a</a></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">VE/VCO2 slope \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">47.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.14, 1.10-1.18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.91, 0.87-0.95 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">LVEF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.94, 0.89-0.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.044 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.76, 0.68-0.84 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Overall AUC \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.91, 0.88-0.95 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="5" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="5" align="left" valign="top">36-month follow-up<a class="elsevierStyleCrossRef" href="#tblfn0040">b</a></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">VE/VCO2 slope \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">89.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.14, 1.11-1.18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.87, 0.81-0.93 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Creatinine levels \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.23, 1.14-4.36 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.020 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.69, 0.65-0.74 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">LVEF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.96, 0.93-0.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.030 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.72, 0.65-0.78 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Overall AUC \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.89, 0.84-0.94 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="5" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="5" align="left" valign="top">60-month follow-up<a class="elsevierStyleCrossRef" href="#tblfn0045">c</a></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">VE/VCO2 slope \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">35.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.11, 1.08-1.16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.87, 0.81-0.92 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Creatinine levels \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.25, 1.27-3.96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.005 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.68, 0.61-0.75 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Δ PetCO2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.39, 0.17-0.89 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.024 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.84, 0.79-0.90 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">LVEF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.97, 0.94-0.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.047 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.72, 0.66-0.79 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Overall AUC \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.89, 0.84-0.94 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="5" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="5" align="left" valign="top">36-month follow-up (low-risk)<a class="elsevierStyleCrossRef" href="#tblfn0050">d</a>,<a class="elsevierStyleCrossRef" href="#tblfn0055">e</a></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Sodium levels \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">18.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.79, 0.71-0.88 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.73, 0.61-0.85 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Creatinine levels \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.75, 1.20-6.29 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.017 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.71, 0.62-0.81 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">LVEF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.94, 0.89-0.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.018 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.72, 0.64-0.80 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Δ PetCO2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.30, 0.10-0.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.039 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.73, 0.63-0.84 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1702749.png" ] ] ] "notaPie" => array:5 [ 0 => array:3 [ "identificador" => "tblfn0035" "etiqueta" => "a" "nota" => "C-index 0.90, 95% CI 0.86-0.94." ] 1 => array:3 [ "identificador" => "tblfn0040" "etiqueta" => "b" "nota" => "C-index 0.88, 95% CI 0.83-0.92." ] 2 => array:3 [ "identificador" => "tblfn0045" "etiqueta" => "c" "nota" => "C-index 0.86, 95% CI 0.82-0.90." ] 3 => array:3 [ "identificador" => "tblfn0050" "etiqueta" => "d" "nota" => "C-index 0.83, 95% CI 0.76-0.91." ] 4 => array:3 [ "identificador" => "tblfn0055" "etiqueta" => "e" "nota" => "Excluding patients with VE/VCO2 slope ≥39.0. AUC for individual variables and for the overall model are presented, for each follow-up time. Δ PetCO2: anaerobic threshold minus baseline end-tidal carbon dioxide partial pressure; AUC: area under the receiving operating characteristic curve; Chi-square: Wald chi-square value; CI: confidence interval; LVEF: left ventricular ejection fraction; VCO2: carbon dioxide production; VE: minute ventilation." ] ] ] "descripcion" => array:1 [ "en" => "Multivariate Cox regression." ] ] 5 => array:8 [ "identificador" => "tbl0020" "etiqueta" => "Table 4" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at4" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "VO2 max: peak oxygen consumption; VCO2: carbon dioxide production; VE: minute ventilation." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">High-risk, n (%)</th><th class="td" title="table-head " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Low-risk, n (%)</th></tr><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Correct \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Incorrect \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Correct \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Incorrect \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">VO2 max ≤10.0 ml/kg/min \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7 (87.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1 (12.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">208 (81.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">47 (18.4) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">VO2 max ≤12.0 ml/kg/min \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10 (71.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4 (28.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">205 (82.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">44 (17.7) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">VE/VCO2 slope ≥39.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27 (79.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7 (20.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">202 (88.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27 (11.8) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1702750.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Proportion of patients correctly and incorrectly classified at 36 months of follow-up." ] ] 6 => array:5 [ "identificador" => "upi0005" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => false "mostrarDisplay" => true "Ecomponente" => array:2 [ "fichero" => "mmc1.doc" "ficheroTamanyo" => 220160 ] ] 7 => array:5 [ "identificador" => "upi0010" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => false "mostrarDisplay" => true "Ecomponente" => array:2 [ "fichero" => "mmc2.doc" "ficheroTamanyo" => 454144 ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:21 [ 0 => array:3 [ "identificador" => "bib0110" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Predicting survival in heart failure: a risk score based on 39372 patients from 30 studies" "autores" => array:1 [ 0 => array:3 [ "colaboracion" => "Meta-Analysis Global Group in Chronic Heart Failure" "etal" => true "autores" => array:3 [ 0 => "S.J. 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Original Article

Optimizing risk stratification in heart failure and the selection of candidates for heart transplantation

Aprimoramento da estratificação de risco na insuficiência cardíaca e da seleção de candidatos a transplantação cardíaca

Tiago Pereira-da-Silvaa,

Corresponding author

tiagopsilva@sapo.pt

Corresponding author.

, Rui M. Soaresa, Ana Luísa Papoilab,c, Iola Pintod,e, Joana Felicianoa, Luís Almeida-Moraisa, Ana Abreua, Rui Cruz Ferreiraa

a Department of Cardiology, Hospital de Santa Marta, Centro Hospitalar de Lisboa Central, Lisbon, Portugal

b Department of Biostatistics and Informatics, NOVA Medical School, Universidade NOVA de Lisboa, Lisbon, Portugal

c Research Unit, Centro Hospitalar de Lisboa Central, Lisbon, Portugal

d Departmental Area of Mathematics, Instituto Superior de Engenharia de Lisboa, Universidade NOVA de Lisboa, Lisbon, Portugal

e Center for Mathematics and Applications, Faculty of Sciences and Technology, Universidade NOVA de Lisboa, Lisbon, Portugal

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          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Event-free survival up to 36 months of follow-up &#40;excluding patients with VE&#47;VCO<span class="elsevierStyleInf">2</span> slope &#8805;39&#46;0&#41; and 95&#37; CI of estimated survival for each subgroup&#44; according to the combination of sodium &#40;136&#46;0 mEq&#47;l&#41;&#44; creatinine &#40;1&#46;0 mg&#47;dl&#41; and variation of end-tidal carbon dioxide partial pressure &#40;0&#46;45 kPa&#41; cut-off values&#46; Group 1&#58; up to one abnormal parameter&#59; group 2&#58; two abnormal parameters&#59; group 3&#58; three abnormal parameters&#46; CI&#58; 95&#37; confidence interval&#59; ISHLT&#58; International Society for Heart and Lung Transplantation&#59; VCO<span class="elsevierStyleInf">2</span>&#58; carbon dioxide production&#59; VE&#58; minute ventilation&#46;</p>"
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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Introduction</span><p id="par0060" class="elsevierStylePara elsevierViewall">A wide variety of predictors of adverse outcome in heart failure &#40;HF&#41; have been described and it can be difficult to choose the most appropriate tools in clinical practice&#46;<a class="elsevierStyleCrossRefs" href="#bib0110"><span class="elsevierStyleSup">1&#44;2</span></a> Risk stratification should be as accurate as possible&#44; particularly when selecting patients for heart transplantation &#40;HTX&#41;&#44; as procedure-related morbidity and mortality are non-negligible and it cannot be offered to all candidates due to the shortage of donors&#46;<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">3</span></a> For ambulatory patients&#44; both the American Heart Association and the International Society for Heart and Lung Transplantation &#40;ISHLT&#41; recommend the use of peak oxygen consumption &#40;VO<span class="elsevierStyleInf">2</span> max&#41; achieved in cardiopulmonary exercise testing &#40;CPET&#41;&#44; with optional use of risk scores in gray zones&#59; VO<span class="elsevierStyleInf">2</span> max &#60;10-12 ml&#47;kg&#47;min is considered a listing criterion for HTX&#46;<a class="elsevierStyleCrossRefs" href="#bib0125"><span class="elsevierStyleSup">4&#44;5</span></a> We believe that risk stratification and referral criteria for HTX can be improved using simple parameters&#46; Additional CPET variables have shown to be accurate for risk stratification&#44; particularly the ventilatory efficiency &#40;VE&#47;VCO<span class="elsevierStyleInf">2</span>&#41; slope&#46;<a class="elsevierStyleCrossRefs" href="#bib0135"><span class="elsevierStyleSup">6&#8211;8</span></a> However&#44; most studies that highlight the value of ergospirometric parameters have focused mainly on clinical and CPET data&#44; without comprehensive assessment of other parameters&#44; and few had long-term follow-up&#46;<a class="elsevierStyleCrossRefs" href="#bib0135"><span class="elsevierStyleSup">6&#8211;9</span></a> Identifying robust criteria for selecting patients for HTX should be based on a comprehensive prospective clinical and complementary assessment&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall">Our aims were to identify the most accurate predictors of adverse events in non-transplanted patients with HF and an approach to optimize the selection of patients for HTX&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Methods</span><p id="par0070" class="elsevierStylePara elsevierViewall">The investigation conforms to the principles outlined in the Declaration of Helsinki&#46; The institutional ethics committee approved the study protocol&#46;</p><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Patient selection and complementary assessment</span><p id="par0075" class="elsevierStylePara elsevierViewall">This single-center analysis included all patients with HF with left ventricular ejection fraction &#40;LVEF&#41; &#8804;40&#37;&#44; in New York Heart Association class II or III&#44; followed in the heart failure clinic of our institution between 2000 and 2009&#46; All patients referred to the heart failure clinic underwent a comprehensive complementary assessment&#46; Clinical&#44; laboratory&#44; electrocardiographic&#44; echocardiographic&#44; and CPET data were prospectively collected&#59; all these exams were performed within a period of one month in each patient&#46;</p><p id="par0080" class="elsevierStylePara elsevierViewall">Patients aged &#60;18 years and those with planned percutaneous coronary revascularization or cardiac surgery&#44; exercise-limiting comorbidities &#40;cerebrovascular disease&#44; musculoskeletal impairment&#44; or severe peripheral vascular disease&#41;&#44; previous HTX&#44; or failure to achieve the anaerobic threshold were excluded&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Cardiopulmonary exercise testing</span><p id="par0085" class="elsevierStylePara elsevierViewall">Maximal symptom-limited treadmill CPET was performed using the modified Bruce protocol &#40;GE Marquette Series 2000 treadmill&#41;&#46; Gas analysis was preceded by calibration of the equipment&#46; Minute ventilation&#44; oxygen uptake and carbon dioxide production were acquired breath-by-breath&#44; using a SensorMedics Vmax 229 gas analyzer&#46; Patients were encouraged to exercise until the respiratory exchange ratio &#40;ratio between carbon dioxide production and oxygen consumption&#41; was &#8805;1&#46;10&#46; VO<span class="elsevierStyleInf">2</span> max was defined as the highest 30-s average achieved during exercise and was normalized for body mass&#44; corrected for fat-free mass in obese patients &#40;body mass index &#62;30 kg&#47;m<span class="elsevierStyleSup">2</span>&#41;&#46; The ventilatory threshold was determined by combining the standard methods &#40;V-slope and ventilatory equivalents&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">10</span></a> The VE&#47;VCO<span class="elsevierStyleInf">2</span> slope was calculated by least squares linear regression&#44; using data acquired throughout the exercise session&#46;<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">10</span></a> Several composite CPET parameters were also calculated&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Follow-up and endpoint</span><p id="par0090" class="elsevierStylePara elsevierViewall">All patients were followed for 60 months from the date of completion of the above-mentioned complementary exams&#46; Patients were assessed for the occurrence of death&#44; HTX or the need for mechanical circulatory support&#46; Data were obtained from outpatient clinic visits and review of medical charts&#44; and were complemented by a standardized telephone interview with all patients at 12&#44; 36 and 60 months of follow-up&#46;</p><p id="par0095" class="elsevierStylePara elsevierViewall">The combined endpoint of cardiac death&#44; urgent HTX &#40;occurring during an unplanned hospitalization for worsening of HF&#44; requiring inotropes&#41; or the need for mechanical circulatory support was analyzed&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Statistical analysis</span><p id="par0100" class="elsevierStylePara elsevierViewall">Categorical data are presented as frequencies &#40;percentages&#41; and continuous variables as mean &#40;standard deviation&#41; or median &#40;25th-75th percentile&#41;&#44; as appropriate&#46; Continuous variables were analyzed using the Student&#39;s t test&#44; or the Mann-Whitney test when normality was not verified by the Kolmogorov-Smirnov test&#59; categorical variables were analyzed using the chi-squared or Fisher&#39;s exact tests&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">Univariate and multivariate Cox regression models were applied to time until the combined endpoint&#44; considering the follow-up times of 12&#44; 36 and 60 months&#46; A complete list of the tested variables and a detailed description of the univariate and multivariate analysis are presented as supplementary material &#40;<a class="elsevierStyleCrossRef" href="#sec0065">Supplementary Tables 1 and 2</a>&#41;&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">The 36-month follow-up period was analyzed to identify a possible approach for selecting patients for HTX&#46;<a class="elsevierStyleCrossRefs" href="#bib0140"><span class="elsevierStyleSup">7&#44;8&#44;11</span></a> To identify the most accurate individual predictor from the multivariate model&#44; the variable with the highest area under the curve &#40;AUC&#41; on receiver operating characteristic &#40;ROC&#41; analysis &#40;VE&#47;VCO<span class="elsevierStyleInf">2</span> slope&#44; post hoc&#41; was selected&#46; To assess the additive value of other predictors to VE&#47;VCO<span class="elsevierStyleInf">2</span> slope&#44; the AUC of VE&#47;VCO<span class="elsevierStyleInf">2</span> slope was compared with the AUC of the model including all predictors of adverse outcome&#46; The DeLong test was used to compare two correlated ROC curves&#46; In addition&#44; continuous net reclassification improvement &#40;NRI&#41; and integrated discrimination improvement &#40;IDI&#41; measures for censored data were calculated&#46;<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">12</span></a></p><p id="par0115" class="elsevierStylePara elsevierViewall">The best cut-off value of VE&#47;VCO<span class="elsevierStyleInf">2</span> slope for identifying high-risk patients was calculated using the martingale residuals&#46; Since HTX can only be offered to a small subgroup of HF patients&#44; we identified another cut-off value that minimized the rate of misclassified high-risk patients&#44; even if sensitivity decreased to reasonable levels&#46;<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">3</span></a> We thus identified a VE&#47;VCO<span class="elsevierStyleInf">2</span> slope threshold that provided a high specificity &#40;at least 90&#37;&#41; with at least 50&#37; sensitivity&#44; using the inverse probability of censoring weighting approach&#46;<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">13</span></a> Subgroups of high- and low-risk patients were created accordingly&#46; Event-free survival rates of both subgroups were estimated using the Kaplan-Meier method and compared using the log-rank test&#46; To assess whether the identified VE&#47;VCO<span class="elsevierStyleInf">2</span> slope threshold is suitable as a potential indication for HTX&#44; two analyses were carried out&#46; Firstly&#44; survival rates of high- and low-risk subgroups of our cohort were compared with survival rates after HTX reported by the ISHLT transplant registry &#40;quarterly data report on survival rates for orthotopic HTX performed in Europe between October 1&#44; 2011 and September 30&#44; 2015&#41;&#44; using a previously reported method&#46;<a class="elsevierStyleCrossRefs" href="#bib0150"><span class="elsevierStyleSup">9&#44;14</span></a> Since the ISHLT reports overall survival&#44; we studied &#40;for this analysis only&#41; time to death from any cause&#44; right censoring in the event of urgent or non-urgent HTX&#46;<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">15</span></a> If the 95&#37; confidence intervals &#40;CI&#41; of estimated survival 36 months after HTX reported by the ISHLT did not overlap with those of high- and low-risk subgroups of our cohort&#44; based on the VE&#47;VCO<span class="elsevierStyleInf">2</span> slope threshold&#44; this can be taken as evidence of significant difference&#46;<a class="elsevierStyleCrossRefs" href="#bib0140"><span class="elsevierStyleSup">7&#44;15</span></a> Secondly&#44; the NRI and IDI were used to compare discretized VE&#47;VCO<span class="elsevierStyleInf">2</span> slope and VO<span class="elsevierStyleInf">2</span> max&#44; considering the combined endpoint for the analysis&#46;</p><p id="par0120" class="elsevierStylePara elsevierViewall">To further stratify prognosis in low-risk patients&#44; high-risk patients were excluded from subsequent analysis and univariate and multivariate Cox regression models were fitted to the low-risk subgroup&#46; Martingale residuals were used to identify cut-off values for the variables that remained in the model and subgroups of high- and low-risk patients were created accordingly&#46; Event-free survival rates of the subgroups were estimated using the Kaplan-Meier method and compared using the Gehan-Breslow-Wilcoxon test&#46;</p><p id="par0125" class="elsevierStylePara elsevierViewall">The level of significance considered was &#945;&#61;0&#46;05&#46; Data were analyzed using SPSS for Windows&#44; version 20&#46;0 &#40;IBM SPSS Inc&#46;&#44; Chicago&#44; IL&#41; and the statistical program R Development Core Team &#40;2014&#41;&#44; R&#58; A language and environment for statistical computing &#40;R Foundation for Statistical Computing&#44; Vienna&#44; Austria&#41;&#46;</p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Results</span><p id="par0130" class="elsevierStylePara elsevierViewall">A total of 263 patients were included&#46; The combined endpoint occurred in 54 patients &#40;20&#46;5&#37;&#41; within 36 months and in 69 &#40;26&#46;2&#37;&#41; within 60 months&#46; The main baseline data are presented in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#44; in which patients with and without events up to 36 months of follow-up are compared and the most important risk predictors identified in univariate Cox regression are presented&#46; Complete data on baseline characteristics and univariate Cox regression are presented in <a class="elsevierStyleCrossRef" href="#sec0065">Supplementary Tables 1 and 2</a>&#44; respectively&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0135" class="elsevierStylePara elsevierViewall">Cumulative adverse events occurring in different follow-up periods are presented in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#46; The independent predictors of adverse events identified in multivariate Cox regression with follow-up times of 12&#44; 36 and 60 months are presented in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#46; At 36 months of follow-up&#44; VE&#47;VCO<span class="elsevierStyleInf">2</span> slope&#44; creatinine levels and LVEF were independent predictors of adverse events&#46; The VE&#47;VCO<span class="elsevierStyleInf">2</span> slope had the highest Wald chi-square value in univariate and multivariate analysis at 36 months and was the parameter with the highest AUC in all multivariate models&#44; considering 12&#44; 36 and 60 months of follow-up&#46; Specifically for the 36-month follow-up period&#44; the AUC of the overall model including all predictors of adverse outcome did not differ significantly from the AUC of the model with VE&#47;VCO<span class="elsevierStyleInf">2</span> slope alone &#40;DeLong test p&#61;0&#46;103&#41;&#46; In addition&#44; the overall NRI was 63&#46;4&#37; &#40;95&#37; CI 33&#46;5-93&#46;4&#37;&#41; and the IDI was 0&#46;019 &#40;95&#37; CI &#91;-0&#46;01&#93;-&#91;0&#46;046&#93;&#41;&#44; when creatinine levels and LVEF were added to VE&#47;VCO<span class="elsevierStyleInf">2</span> slope&#59; as the 95&#37; CI of IDI includes the null value&#44; the improvement in model performance is negligible&#46; Since the other predictors included in the model &#40;creatinine levels and LVEF&#41; did not add significantly to VE&#47;VCO<span class="elsevierStyleInf">2</span> slope for risk prediction&#44; only VE&#47;VCO<span class="elsevierStyleInf">2</span> slope was selected to obtain a cut-off value for clinical use&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0140" class="elsevierStylePara elsevierViewall">Based on the martingale residuals&#44; the best estimated cut-off value for VE&#47;VCO<span class="elsevierStyleInf">2</span> slope to identify patients at higher risk at 36 months of follow-up was 32&#46;0 &#40;specificity 80&#37;&#44; sensitivity 83&#37;&#41; &#40;<a class="elsevierStyleCrossRef" href="#sec0065">Supplementary Figure 1</a>&#41;&#46; However&#44; a threshold of 39&#46;0 provided higher specificity &#40;97&#37;&#41;&#44; with 52&#37; sensitivity&#46; The estimated 36-month survival for high-risk &#40;VE&#47;VCO<span class="elsevierStyleInf">2</span> slope &#8805;39&#46;0&#41; and low-risk &#40;VE&#47;VCO<span class="elsevierStyleInf">2</span> slope &#60;39&#46;0&#41; patients was significantly different &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Figure 1</a>&#41;&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0145" class="elsevierStylePara elsevierViewall">A threshold of 39&#46;0 for VE&#47;VCO<span class="elsevierStyleInf">2</span> slope was assessed as a potential listing criterion for HTX&#46; Firstly&#44; the 95&#37; CIs of estimated survival &#40;considering all-cause death&#41; for high- and low-risk subgroups did not overlap with those of post-HTX reported by the ISHLT&#46;<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">15</span></a> Secondly&#44; the VE&#47;VCO<span class="elsevierStyleInf">2</span> slope had a higher AUC than VO<span class="elsevierStyleInf">2</span> max&#44; considering both as continuous variables &#40;AUC of VO<span class="elsevierStyleInf">2</span> max 0&#46;79&#44; 95&#37; CI 0&#46;72-0&#46;87&#59; DeLong test for comparison p&#61;0&#46;009&#41;&#46; Moreover&#44; there was a significant improvement in the percentage of correct classification using the VE&#47;VCO<span class="elsevierStyleInf">2</span> slope threshold of 39&#46;0&#44; in comparison to discretized VO<span class="elsevierStyleInf">2</span> max &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41;&#58; considering the VO<span class="elsevierStyleInf">2</span> max threshold of 10&#46;0 ml&#47;kg&#47;min&#44; the overall NRI and IDI were 82&#46;2&#37; &#40;95&#37; CI 52&#46;3-112&#46;1&#37;&#41; and 0&#46;278 &#40;95&#37; CI 0&#46;182-0&#46;373&#41;&#44; respectively&#59; considering the VO<span class="elsevierStyleInf">2</span> max threshold of 12&#46;0 ml&#47;kg&#47;min&#44; the overall NRI and IDI were 93&#46;3&#37; &#40;95&#37; CI 63&#46;4-123&#46;2&#37;&#41; and 0&#46;226 &#40;95&#37; CI 0&#46;141-0&#46;311&#41;&#44; respectively&#46; Since the data consistently favored the use of VE&#47;VCO<span class="elsevierStyleInf">2</span> slope as an indication for HTX&#44; high-risk patients &#40;VE&#47;VCO<span class="elsevierStyleInf">2</span> slope &#8805;39&#46;0&#41; were excluded from subsequent analysis&#46; In the other 229 patients&#44; 27 &#40;11&#46;8&#37;&#41; events occurred during 36 months of follow-up&#46; Sodium and creatinine levels&#44; LVEF&#44; and variation achieved in CPET &#40;anaerobic threshold minus baseline&#41; of the end-tidal carbon dioxide partial pressure &#40;&#916; PetCO<span class="elsevierStyleInf">2</span>&#41; were independent predictors of adverse events at 36 months of follow-up &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#41;&#46; The AUC was similar for these predictors&#46; For LVEF&#44; the flatness of the martingale residuals smoother did not enable a suitable cut-off point to be identified that discriminated high- and low-risk patients &#40;<a class="elsevierStyleCrossRef" href="#sec0065">Supplementary Figure 2</a>&#41;&#59; sodium &#8804;136&#46;0 mEq&#47;l&#44; creatinine &#8805;1&#46;0 mg&#47;dl and &#916; PetCO<span class="elsevierStyleInf">2</span> &#8804;0&#46;45 kPa &#40;3&#46;4 mmHg&#41; were associated with higher risk of adverse events &#40;specificity 63&#37;&#44; 61&#37; and 63&#37;&#44; sensitivity 77&#37;&#44; 74&#37; and 74&#37;&#44; respectively&#41;&#46; Eight subgroups were created according to the three mentioned cut-off values &#40;<a class="elsevierStyleCrossRef" href="#sec0065">Supplementary Figure 3</a>&#41;&#46; Prognosis was similar for patients with up to one variable &#40;sodium&#44; creatinine or &#916; PetCO<span class="elsevierStyleInf">2</span>&#41; with abnormal values &#40;classified according to the thresholds identified&#41;&#59; prognosis was similar for patients with two variables with abnormal values&#44; and event-free survival was worst when the three variables were classified as abnormal&#46; Three groups were created accordingly &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Figure 2</a>&#41;&#59; prognosis was significantly different for the three categories&#46;</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Discussion</span><p id="par0150" class="elsevierStylePara elsevierViewall">The most accurate predictor of adverse outcome in patients with HF with reduced LVEF was VE&#47;VCO<span class="elsevierStyleInf">2</span> slope and the best threshold for identifying patients who may benefit from HTX was 39&#46;0&#46; Sodium levels&#44; creatinine levels and &#916; PetCO<span class="elsevierStyleInf">2</span> were able to identify low-risk patients with excellent outcome&#46;</p><p id="par0155" class="elsevierStylePara elsevierViewall">Risk stratification in HF and selecting patients for HTX are challenging&#46; Mancini et al&#46;<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">18</span></a> showed in an ancillary study that VO<span class="elsevierStyleInf">2</span> max is a valuable parameter for selecting patients for HTX&#44; and subsequently refined their cut-off values&#46;<a class="elsevierStyleCrossRefs" href="#bib0160"><span class="elsevierStyleSup">11&#44;19</span></a> Currently&#44; the American Heart Association recommends listing ambulatory patients for HTX when VO<span class="elsevierStyleInf">2</span> max is &#60;10 ml&#47;kg&#47;min with achievement of anaerobic metabolism&#44; and to defer when VO<span class="elsevierStyleInf">2</span> max is &#62;14 ml&#47;kg&#47;min&#46;<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">4</span></a> Mancini et al&#46;<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">19</span></a> proposed a similar decision algorithm&#44; also recommending assessment using the Heart Failure Survival Score &#40;HFSS&#41;&#46; The ISHLT recommends listing when VO<span class="elsevierStyleInf">2</span> max is &#60;12 ml&#47;kg&#47;min on beta-blockers&#44; deferring when it is &#62;14 ml&#47;kg&#47;min&#44; and using the HFSS in the gray zone&#46;<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">5</span></a> Only in the presence of a submaximal CPET should VE&#47;VCO<span class="elsevierStyleInf">2</span> slope be considered as a listing criterion&#44; according to the ISHLT guidelines&#46;<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">5</span></a> Risk stratification and patient selection for HTX could probably be improved&#46;<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">7</span></a> However&#44; the use of randomized controlled trials to address the issue of listing criteria is hindered by ethical and social considerations&#46; In this context&#44; data from robust registries on non-transplanted HF patients receiving contemporary pharmacological and device therapy are of great value&#46;</p><p id="par0160" class="elsevierStylePara elsevierViewall">We evaluated an extensive range of clinical&#44; laboratory&#44; electrocardiographic&#44; echocardiographic&#44; and CPET parameters as potential predictors of adverse outcome&#46; The single best parameter of all those studied was VE&#47;VCO<span class="elsevierStyleInf">2</span> slope&#44; yielding the highest Wald chi-square value and the highest AUC at 12&#44; 36 and 60 months of follow-up&#44; and with even more discriminative power than the HFSS&#44; which combines different variables&#46; Of note&#44; VO<span class="elsevierStyleInf">2</span> max did not remain in any multivariate model in our cohort&#46; The 60-month follow-up period was not used to identify an approach for selecting patients for HTX&#44; since prognostic reassessment should be undertaken earlier&#46;<a class="elsevierStyleCrossRefs" href="#bib0140"><span class="elsevierStyleSup">7&#44;8</span></a> Nevertheless&#44; the long-term follow-up carried out confirmed the consistently higher accuracy of VE&#47;VCO<span class="elsevierStyleInf">2</span> slope over a long period&#44; in comparison to other parameters&#46; This finding has not been properly addressed in previous studies&#46;<a class="elsevierStyleCrossRefs" href="#bib0135"><span class="elsevierStyleSup">6&#8211;8</span></a> Arena et al&#46;<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">6</span></a> showed that the risk of adverse events increases continuously over different categories of VE&#47;VCO<span class="elsevierStyleInf">2</span> slope&#46; However&#44; thresholds are useful for clinical practice&#44; and VE&#47;VCO<span class="elsevierStyleInf">2</span> slope values of 34&#46;0 and 35&#46;0 have been proposed as optimal criteria for classifying patients with HF as high- and low-risk&#46;<a class="elsevierStyleCrossRefs" href="#bib0130"><span class="elsevierStyleSup">5&#44;14</span></a> In line with these thresholds&#44; the risk of adverse events began to rise for values above 32&#46;0 in our cohort&#44; as shown by analysis of the martingale residuals&#46; Although the specificity for this threshold was not low &#40;80&#37;&#41;&#44; a non-negligible proportion of patients would be classified as high-risk even though they would not experience an adverse outcome&#46; If this was considered a listing criterion for HTX&#44; issues related to the shortage of donors and to the morbidity and mortality following HTX might arise&#44; by listing patients who were at a less severe stage of HF&#46; Therefore&#44; the threshold of 39&#46;0&#44; which provides very high specificity with reasonable sensitivity&#44; may be more appropriate for selecting patients for HTX than lower cut-off values&#46;<a class="elsevierStyleCrossRefs" href="#bib0130"><span class="elsevierStyleSup">5&#44;14</span></a> Freedom from the combined endpoint at 36 months of follow-up was very low &#40;19&#46;3&#37;&#41; for patients with VE&#47;VCO<span class="elsevierStyleInf">2</span> slope &#8805;39&#46;0&#46; Even though this threshold was not primarily identified to predict total mortality&#44; the 95&#37; CI of estimated overall survival of high- and low-risk subgroups did not overlap with those of post-HTX reported by the ISHLT&#46;<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">15</span></a> This finding suggests that&#44; for our cohort&#44; survival of hypothetically transplanted patients would be better than survival of non-transplanted high-risk patients and worse than survival of non-transplanted low-risk patients&#46; In addition&#44; the threshold of 39&#46;0 for VE&#47;VCO<span class="elsevierStyleInf">2</span> slope was more accurate than the cut-off values of 10 or 12 ml&#47;kg&#47;min for VO<span class="elsevierStyleInf">2</span> max&#44; which are recommended as listing criteria&#46;<a class="elsevierStyleCrossRefs" href="#bib0125"><span class="elsevierStyleSup">4&#44;5</span></a> VE&#47;VCO<span class="elsevierStyleInf">2</span> slope has previously been reported as providing a discriminative power at least as good as VO<span class="elsevierStyleInf">2</span> max for predicting adverse events&#46;<a class="elsevierStyleCrossRefs" href="#bib0135"><span class="elsevierStyleSup">6&#44;9</span></a> Nevertheless&#44; the majority of studies that highlighted the value of VE&#47;VCO<span class="elsevierStyleInf">2</span> slope did not assess this parameter in the light of a comprehensive assessment of clinical&#44; laboratory&#44; electrocardiographic&#44; echocardiographic and CPET parameters&#44; and few had a long-term follow-up&#46;<a class="elsevierStyleCrossRefs" href="#bib0135"><span class="elsevierStyleSup">6&#8211;8</span></a> Compared to previous studies&#44; we carried out a more comprehensive &#40;and prospective&#41; baseline assessment&#44; with a long-term follow-up&#44; and employing a robust statistical analysis with consistent results&#46; Based on our results&#44; patients with VE&#47;VCO<span class="elsevierStyleInf">2</span> slope &#8805;39&#46;0 may benefit from HTX&#46;</p><p id="par0165" class="elsevierStylePara elsevierViewall">For low-risk non-transplanted patients with sodium levels &#62;136&#46;0 mEq&#47;l&#44; creatinine levels &#60;1&#46;0 mg&#47;dl and &#916; PetCO<span class="elsevierStyleInf">2</span> &#62;0&#46;45 kPa &#40;3&#46;4 mmHg&#41;&#44; or patients with up to one of these variables classified as abnormal&#44; the prognosis was excellent and total mortality was lower than that reported for post-HTX&#46;<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">15</span></a> Sodium and creatinine levels are known independent predictors of adverse events in HF and are included in risk scores such as the HFSS and the Meta-Analysis Global Group in Chronic Heart Failure score&#46;<a class="elsevierStyleCrossRefs" href="#bib0110"><span class="elsevierStyleSup">1&#44;2</span></a> PetCO<span class="elsevierStyleInf">2</span> at rest and at the anaerobic threshold were shown to stratify risk beyond the VE&#47;VCO<span class="elsevierStyleInf">2</span> slope&#44; and combining them into a single parameter &#40;&#916; PetCO<span class="elsevierStyleInf">2</span>&#41; may be more practical and accurate&#46;<a class="elsevierStyleCrossRefs" href="#bib0205"><span class="elsevierStyleSup">20&#44;21</span></a> We suggest that particular attention should be paid to sodium levels&#44; creatinine levels and &#916; PetCO<span class="elsevierStyleInf">2</span>&#44; in addition to VE&#47;VCO<span class="elsevierStyleInf">2</span> slope&#44; particularly for identifying low-risk patients in clinical practice&#46;</p><p id="par0170" class="elsevierStylePara elsevierViewall">Some limitations of the study should be acknowledged&#46; Firstly&#44; the analyzed cohort was not large&#46; However&#44; it was possible to identify the most important independent predictors of adverse outcome in HF and a strategy for optimizing the selection of patients for HTX&#44; and the results were consistent using different statistical analyses&#46; The sample size is similar to those of other studies that highlighted the value of CPET parameters&#44; including for the selection of patients for HTX&#46;<a class="elsevierStyleCrossRefs" href="#bib0135"><span class="elsevierStyleSup">6&#44;14&#44;18&#44;20&#44;21</span></a> Secondly&#44; this was a single-center study&#46; Nevertheless&#44; this meant that the CPET protocol was consistent in all cases&#44; and may have reduced the number of physicians responsible for the interpretation of the exam&#44; reducing interobserver variability&#46; Thirdly&#44; listing for HTX is a complex and multidisciplinary decision and should not rely solely on &#8216;magic numbers&#8217; of specific parameters from complementary exams&#59; however&#44; thresholds are useful in clinical practice&#44; as pointed out above&#46; In addition&#44; the aim was not to replace but to potentially optimize current listing criteria for HTX&#46; The decision threshold we propose is in line with current practice in different centers&#44; where clinical decisions are supported by VE&#47;VCO<span class="elsevierStyleInf">2</span> slope data in addition to VO<span class="elsevierStyleInf">2</span> max&#44; even though current guidelines do not address this approach&#46;<a class="elsevierStyleCrossRefs" href="#bib0125"><span class="elsevierStyleSup">4&#44;5&#44;7</span></a> A further validation study would certainly be useful&#46;</p></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Conclusions</span><p id="par0175" class="elsevierStylePara elsevierViewall">Among a large variety of predictors of adverse outcome in ambulatory patients with HF with reduced LVEF&#44; the most accurate was VE&#47;VCO<span class="elsevierStyleInf">2</span> slope&#46; Patients with VE&#47;VCO<span class="elsevierStyleInf">2</span> slope of 39&#46;0 or higher may benefit from HTX&#46; Beyond the VE&#47;VCO<span class="elsevierStyleInf">2</span> slope&#44; sodium levels&#44; creatinine levels and &#916; PetCO<span class="elsevierStyleInf">2</span> were able to identify patients with excellent outcome&#46;</p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Funding</span><p id="par0180" class="elsevierStylePara elsevierViewall">None&#46;</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Conflicts of interest</span><p id="par0185" class="elsevierStylePara elsevierViewall">The authors have no conflicts of interest to declare&#46;</p></span></span>"
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          "identificador" => "xres1005649"
          "titulo" => "Abstract"
          "secciones" => array:4 [
            0 => array:2 [
              "identificador" => "abst0005"
              "titulo" => "Introduction and Aims"
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        1 => array:2 [
          "identificador" => "xpalclavsec965438"
          "titulo" => "Keywords"
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            0 => array:2 [
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              "titulo" => "Introdu&#231;&#227;o e objetivos"
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              "titulo" => "M&#233;todos"
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              "titulo" => "Resultados"
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              "titulo" => "Conclus&#245;es"
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          "titulo" => "Palavras-chave"
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            0 => array:2 [
              "identificador" => "sec0015"
              "titulo" => "Patient selection and complementary assessment"
            ]
            1 => array:2 [
              "identificador" => "sec0020"
              "titulo" => "Cardiopulmonary exercise testing"
            ]
            2 => array:2 [
              "identificador" => "sec0025"
              "titulo" => "Follow-up and endpoint"
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              "titulo" => "Statistical analysis"
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          "titulo" => "Conflicts of interest"
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          "titulo" => "References"
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    "pdfFichero" => "main.pdf"
    "tienePdf" => true
    "fechaRecibido" => "2017-01-22"
    "fechaAceptado" => "2017-06-18"
    "PalabrasClave" => array:2 [
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        0 => array:4 [
          "clase" => "keyword"
          "titulo" => "Keywords"
          "identificador" => "xpalclavsec965438"
          "palabras" => array:6 [
            0 => "Cardiopulmonary exercise testing"
            1 => "Heart failure"
            2 => "Heart transplantation"
            3 => "Peak oxygen consumption"
            4 => "Risk stratification"
            5 => "Ventilatory efficiency slope"
          ]
        ]
      ]
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        0 => array:4 [
          "clase" => "keyword"
          "titulo" => "Palavras-chave"
          "identificador" => "xpalclavsec965437"
          "palabras" => array:6 [
            0 => "Prova de esfor&#231;o cardiorrespirat&#243;ria"
            1 => "Insufici&#234;ncia card&#237;aca"
            2 => "Transplanta&#231;&#227;o card&#237;aca"
            3 => "Consumo de oxig&#233;nio de pico"
            4 => "Estratifica&#231;&#227;o de risco"
            5 => "Declive da efici&#234;ncia ventilat&#243;ria"
          ]
        ]
      ]
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    "tieneResumen" => true
    "resumen" => array:2 [
      "en" => array:3 [
        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction and Aims</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Selecting patients for heart transplantation is challenging&#46; We aimed to identify the most important risk predictors in heart failure and an approach to optimize the selection of candidates for heart transplantation&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Ambulatory patients followed in our center with symptomatic heart failure and left ventricular ejection fraction &#8804;40&#37; prospectively underwent a comprehensive baseline assessment including clinical&#44; laboratory&#44; electrocardiographic&#44; echocardiographic&#44; and cardiopulmonary exercise testing parameters&#46; All patients were followed for 60 months&#46; The combined endpoint was cardiac death&#44; urgent heart transplantation or need for mechanical circulatory support&#44; up to 36 months&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">In the 263 enrolled patients &#40;75&#37; male&#44; age 54&#177;12 years&#41;&#44; 54 events occurred&#46; The independent predictors of adverse outcome were ventilatory efficiency &#40;VE&#47;VCO<span class="elsevierStyleInf">2</span>&#41; slope &#40;HR 1&#46;14&#44; 95&#37; CI 1&#46;11-1&#46;18&#41;&#44; creatinine level &#40;HR 2&#46;23&#44; 95&#37; CI 1&#46;14-4&#46;36&#41;&#44; and left ventricular ejection fraction &#40;HR 0&#46;96&#44; 95&#37; CI 0&#46;93-0&#46;99&#41;&#46; VE&#47;VCO<span class="elsevierStyleInf">2</span> slope was the most accurate risk predictor at any follow-up time analyzed &#40;up to 60 months&#41;&#46; The threshold of 39&#46;0 yielded high specificity &#40;97&#37;&#41;&#44; discriminated a worse or better prognosis than that reported for post-heart transplantation&#44; and outperformed peak oxygen consumption thresholds of 10&#46;0 or 12&#46;0 ml&#47;kg&#47;min&#46; For low-risk patients &#40;VE&#47;VCO<span class="elsevierStyleInf">2</span> slope &#60;39&#46;0&#41;&#44; sodium and creatinine levels and variations in end-tidal carbon dioxide partial pressure on exercise identified those with excellent prognosis&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">VE&#47;VCO<span class="elsevierStyleInf">2</span> slope was the most accurate parameter for risk stratification in patients with heart failure and reduced ejection fraction&#46; Those with VE&#47;VCO<span class="elsevierStyleInf">2</span> slope &#8805;39&#46;0 may benefit from heart transplantation&#46;</p></span>"
        "secciones" => array:4 [
          0 => array:2 [
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            "titulo" => "Introduction and Aims"
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            "titulo" => "Methods"
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            "titulo" => "Results"
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            "titulo" => "Conclusions"
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      "pt" => array:3 [
        "titulo" => "Resumo"
        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Introdu&#231;&#227;o e objetivos</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">A sele&#231;&#227;o de doentes para transplanta&#231;&#227;o card&#237;aca &#233; dif&#237;cil&#46; Procur&#225;mos identificar os preditores de risco mais relevantes na insufici&#234;ncia card&#237;aca e uma abordagem para aprimorar a sele&#231;&#227;o de candidatos a transplanta&#231;&#227;o&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">M&#233;todos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Doentes sintom&#225;ticos com insufici&#234;ncia card&#237;aca e fra&#231;&#227;o de eje&#231;&#227;o ventricular esquerda &#8804; 40&#37;&#44; ambulat&#243;rios&#44; seguidos no nosso centro&#44; completaram prospetivamente uma avalia&#231;&#227;o basal abrangente&#44; inclusive par&#226;metros cl&#237;nicos&#44; laboratoriais&#44; eletrocardiogr&#225;ficos&#44; ecocardiogr&#225;ficos e prova de esfor&#231;o cardiorrespirat&#243;ria&#59; foram seguidos por 60 meses&#46; <span class="elsevierStyleItalic">Endpoint</span> combinado&#58; morte de causa card&#237;aca&#44; transplanta&#231;&#227;o urgente ou necessidade de assist&#234;ncia mec&#226;nica&#44; at&#233; aos 36 meses&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Nos 263 doentes inclu&#237;dos &#40;75&#37; homens&#44; 54 &#177;12 anos&#41; ocorreram 54 eventos&#46; O declive da efici&#234;ncia ventilat&#243;ria &#40;declive VE&#47;VCO2&#41; &#40;HR 1&#44;14&#44; IC 95&#37; 1&#44;11-1&#44;18&#41;&#44; a creatinina &#40;HR 2&#44;23&#44; IC 95&#37; 1&#44;14-4&#44;36&#41; e a fra&#231;&#227;o de eje&#231;&#227;o ventricular esquerda &#40;HR 0&#44;96&#44; IC 95&#37; 0&#44;93-0&#44;99&#41; foram preditores independentes de eventos&#46; O declive VE&#47;VCO2 foi o melhor preditor em qualquer per&#237;odo analisado &#40;at&#233; aos 60 meses&#41;&#46; O limiar 39&#44;0 apresentou elevada especificidade &#40;97&#37;&#41;&#44; discriminou um progn&#243;stico melhor ou pior do que o reportado no p&#243;s-transplante card&#237;aco e superou os limiares 10&#44;0 ou 12&#44;0 mL&#47;kg&#47;min de consumo de oxig&#233;nio de pico&#46; Em doentes de baixo risco &#40;declive VE&#47;VCO2 &#60;39&#44;0&#41; o s&#243;dio&#44; a creatinina e a varia&#231;&#227;o no exerc&#237;cio da press&#227;o parcial de di&#243;xido de carbono expirado identificaram aqueles com excelente pron&#243;stico&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclus&#245;es</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">O declive VE&#47;VCO2 foi o melhor preditor de risco em doentes com insufici&#234;ncia card&#237;aca e fra&#231;&#227;o de eje&#231;&#227;o reduzida&#46; Doentes com declive VE&#47;VCO2 &#8805;39&#44;0 poder&#227;o beneficiar de transplanta&#231;&#227;o card&#237;aca&#46;</p></span>"
        "secciones" => array:4 [
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            "identificador" => "abst0025"
            "titulo" => "Introdu&#231;&#227;o e objetivos"
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            "titulo" => "M&#233;todos"
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            "titulo" => "Resultados"
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            "apendice" => "<p id="par0195" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="upi0005"></elsevierMultimedia><elsevierMultimedia ident="upi0010"></elsevierMultimedia></p>"
            "etiqueta" => "Appendix A"
            "titulo" => "Supplementary material"
            "identificador" => "sec0065"
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    "nomenclatura" => array:1 [
      0 => array:3 [
        "identificador" => "nom0005"
        "titulo" => "<span class="elsevierStyleSectionTitle" id="sect0065">List of abbreviations</span>"
        "listaDefinicion" => array:1 [
          0 => array:1 [
            "definicion" => array:11 [
              0 => array:2 [
                "termino" => "&#916; PetCO<span class="elsevierStyleInf">2</span>"
                "descripcion" => "<p id="par0200" class="elsevierStylePara elsevierViewall">variation of end-tidal carbon dioxide partial pressure</p>"
              ]
              1 => array:2 [
                "termino" => "CI"
                "descripcion" => "<p id="par0205" class="elsevierStylePara elsevierViewall">confidence interval</p>"
              ]
              2 => array:2 [
                "termino" => "CPET"
                "descripcion" => "<p id="par0005" class="elsevierStylePara elsevierViewall">cardiopulmonary exercise testing</p>"
              ]
              3 => array:2 [
                "termino" => "HF"
                "descripcion" => "<p id="par0010" class="elsevierStylePara elsevierViewall">heart failure</p>"
              ]
              4 => array:2 [
                "termino" => "HTX"
                "descripcion" => "<p id="par0015" class="elsevierStylePara elsevierViewall">heart transplantation</p>"
              ]
              5 => array:2 [
                "termino" => "IDI"
                "descripcion" => "<p id="par0020" class="elsevierStylePara elsevierViewall">integrated discrimination improvement</p>"
              ]
              6 => array:2 [
                "termino" => "ISHLT"
                "descripcion" => "<p id="par0025" class="elsevierStylePara elsevierViewall">International Society for Heart and Lung Transplantation</p>"
              ]
              7 => array:2 [
                "termino" => "LVEF"
                "descripcion" => "<p id="par0030" class="elsevierStylePara elsevierViewall">left ventricular ejection fraction</p>"
              ]
              8 => array:2 [
                "termino" => "NRI"
                "descripcion" => "<p id="par0035" class="elsevierStylePara elsevierViewall">net reclassification improvement</p>"
              ]
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                "termino" => "VO<span class="elsevierStyleInf">2</span> max"
                "descripcion" => "<p id="par0040" class="elsevierStylePara elsevierViewall">peak oxygen consumption</p>"
              ]
              10 => array:2 [
                "termino" => "VE&#47;VCO<span class="elsevierStyleInf">2</span> slope"
                "descripcion" => "<p id="par0045" class="elsevierStylePara elsevierViewall">ventilatory efficiency slope</p>"
              ]
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        "descripcion" => array:1 [
          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Event-free survival up to 36 months of follow-up according to VE&#47;VCO<span class="elsevierStyleInf">2</span> slope threshold of 39&#46;0&#44; and 95&#37; CI of estimated survival for each subgroup&#46; CI&#58; 95&#37; confidence interval&#59; ISHLT&#58; International Society for Heart and Lung Transplantation&#59; VCO<span class="elsevierStyleInf">2</span>&#58; carbon dioxide production&#59; VE&#58; minute ventilation&#46;</p>"
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      1 => array:7 [
        "identificador" => "fig0010"
        "etiqueta" => "Figure 2"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
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        "descripcion" => array:1 [
          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Event-free survival up to 36 months of follow-up &#40;excluding patients with VE&#47;VCO<span class="elsevierStyleInf">2</span> slope &#8805;39&#46;0&#41; and 95&#37; CI of estimated survival for each subgroup&#44; according to the combination of sodium &#40;136&#46;0 mEq&#47;l&#41;&#44; creatinine &#40;1&#46;0 mg&#47;dl&#41; and variation of end-tidal carbon dioxide partial pressure &#40;0&#46;45 kPa&#41; cut-off values&#46; Group 1&#58; up to one abnormal parameter&#59; group 2&#58; two abnormal parameters&#59; group 3&#58; three abnormal parameters&#46; CI&#58; 95&#37; confidence interval&#59; ISHLT&#58; International Society for Heart and Lung Transplantation&#59; VCO<span class="elsevierStyleInf">2</span>&#58; carbon dioxide production&#59; VE&#58; minute ventilation&#46;</p>"
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                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Variable&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">All patients&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Events<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">No events<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">p&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Chi-square&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Hazard ratio&#44;<br>95&#37; CI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">p&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry  " colspan="8" align="left" valign="top"><span class="elsevierStyleItalic">Clinical and electrocardiographic data</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Age &#40;years&#41;<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">54 &#40;12&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">54 &#40;12&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">53 &#40;12&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;718&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;00&#44; 0&#46;98-1&#46;02&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;781&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Male<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">44 &#40;81&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">153 &#40;73&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;141&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;61&#44; 0&#46;33-1&#46;15&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;125&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Diabetes<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">54 &#40;21&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8 &#40;15&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">46 &#40;22&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;248&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;12&#44; 0&#46;60-2&#46;08&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;728&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Ischemic etiology<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">97 &#40;37&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">28 &#40;52&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">69 &#40;33&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;009&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;06&#44; 1&#46;13-3&#46;75&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;018&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>NYHA II &#40;vs&#46; III&#41;<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">200 &#40;76&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">28 &#40;52&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">172 &#40;82&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">37&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;22&#44; 0&#46;12-0&#46;42&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Sinus rhythm<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">214 &#40;81&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">36 &#40;67&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">178 &#40;85&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;003&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">11&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;52&#44; 1&#46;28-4&#46;96&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;008&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Loop diuretic<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">234 &#40;89&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">54 &#40;100&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">180 &#40;86&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;002&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">24&#46;9&#44; 1&#46;1-546&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;041&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>ACEi&#47;ARB<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">255 &#40;97&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">54 &#40;100&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">201 &#40;96&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;309&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;05&#44; 0&#46;01-12&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;285&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Betablocker<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">233 &#40;89&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">48 &#40;89&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">185 &#40;89&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;999&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;41&#44; 0&#46;81-2&#46;43&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;224&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Aldosterone receptor blocker<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">176 &#40;67&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">43 &#40;80&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">133 &#40;64&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;035&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">5&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;00&#44; 1&#46;12-3&#46;54&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;018&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Baseline CRT<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">72 &#40;27&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">14 &#40;26&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">58 &#40;28&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;342&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;72&#44; 0&#46;64-3&#46;36&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;462&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Baseline ICD<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">85 &#40;32&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">18 &#40;33&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">67 &#40;32&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;117&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;41&#44; 0&#46;79-2&#46;64&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;236&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="8" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="8" align="left" valign="top"><span class="elsevierStyleItalic">Laboratory data</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Creatinine &#40;mg&#47;dl&#41;<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;1 &#40;0&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;2 &#40;0&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;1 &#40;0&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">15&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3&#46;93&#44; 1&#46;66-9&#46;26&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Sodium &#40;mEq&#47;l&#41;<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">137 &#40;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">134 &#40;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">137 &#40;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">62&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;73&#44; 0&#46;66-0&#46;81&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>NT-proBNP &#40;pg&#47;ml&#41;<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2304 &#40;2821&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4269 &#40;4724&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1898 &#40;2029&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">38&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;01&#44; 1&#46;00-1&#46;01&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Elevated troponin T<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">37 &#40;14&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">13 &#40;24&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">24 &#40;11&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;004&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">14&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3&#46;54&#44; 1&#46;54-8&#46;12&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;003&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="8" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="8" align="left" valign="top"><span class="elsevierStyleItalic">Echocardiographic data</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>LVEDD &#40;mm&#47;m<span class="elsevierStyleSup">2</span>&#41;<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">39 &#40;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">42 &#40;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">39 &#40;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;006&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;16&#44; 0&#46;04-0&#46;64&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;010&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>LVEF &#40;&#37;&#41;<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">28 &#40;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">23 &#40;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">28 &#40;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">26&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;92&#44; 0&#46;90-0&#46;95&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>MR<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">42 &#40;16&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">9 &#40;17&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">33 &#40;16&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;988&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;92&#44; 0&#46;30-1&#46;55&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;872&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>RVSD<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">42 &#40;16&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">19 &#40;35&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">23 &#40;11&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">37&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">7&#46;09&#44; 3&#46;28-15&#46;33&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="8" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="8" align="left" valign="top"><span class="elsevierStyleItalic">Cardiopulmonary exercise testing data</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>HR recovery &#40;1st minute&#41; &#40;min&#41;<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">d</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">18 &#40;13-29&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">13 &#40;8-18&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">19 &#40;15-30&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">33&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;90&#44; 0&#46;85-0&#46;93&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>&#916; double product &#40;mmHg&#47;min&#41;<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">11911 &#40;5374&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8564 &#40;4443&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">12619 &#40;5547&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">26&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;00&#44; 1&#46;00-1&#46;00&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Peak RER<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;10 &#40;0&#46;10&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;13 &#40;0&#46;10&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;09 &#40;0&#46;09&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;008&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">5&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">45&#46;75&#44; 2&#46;59-808&#46;94&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;011&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>VO<span class="elsevierStyleInf">2</span> max &#40;ml&#47;kg&#47;min&#41;<span class="elsevierStyleSup">e&#44;</span><a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">20&#46;0 &#40;5&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">15&#46;6 &#40;4&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">21&#46;1 &#40;5&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">56&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;78&#44; 0&#46;71-0&#46;85&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>VO<span class="elsevierStyleInf">2</span> max &#40;&#37; predicted&#41;<span class="elsevierStyleSup">e&#44;</span><a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">67 &#40;15&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">51 &#40;14&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">71 &#40;16&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">69&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;91&#44; 0&#46;81-0&#46;94&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Circulatory power &#40;mmHg&#47;ml&#47;kg&#47;min&#41;<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3115 &#40;1123&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2185 &#40;895&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3289 &#40;1132&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">48&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;99&#44; 0&#46;99-0&#46;99&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Peak oxygen pulse &#40;&#37; predicted&#41;<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">91 &#40;30&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">74 &#40;23&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">95 &#40;30&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">28&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;97&#44; 0&#46;96-0&#46;98&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>OUES<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;8 &#40;0&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;4 &#40;0&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;9 &#40;0&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">49&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;11&#44; 0&#46;05-0&#46;27&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>AT-VO<span class="elsevierStyleInf">2</span> &#40;ml&#47;kg&#47;min&#41;<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">16&#46;1 &#40;4&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">12&#46;6 &#40;3&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">17&#46;0 &#40;4&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">61&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;74&#44; 0&#46;66-0&#46;81&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>VE&#47;VCO<span class="elsevierStyleInf">2</span> slope<span class="elsevierStyleSup">f&#44;</span><a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">31 &#40;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">40 &#40;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">29 &#40;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">139&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;27&#44; 1&#46;19-1&#46;35&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Peak VE&#47;VCO<span class="elsevierStyleInf">2</span><span class="elsevierStyleSup">f&#44;</span><a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">35 &#40;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">42 &#40;10&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">33 &#40;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">76&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;14&#44; 1&#46;09-1&#46;19&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>AT VE&#47;VCO<span class="elsevierStyleInf">2</span><span class="elsevierStyleSup">f&#44;</span><a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">33 &#40;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">40 &#40;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">31 &#40;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">78&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;17&#44; 1&#46;08-1&#46;23&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>VE&#47;VCO<span class="elsevierStyleInf">2</span> slope&#47;VO<span class="elsevierStyleInf">2</span> max &#40;ml&#47;kg&#47;min&#41;<span class="elsevierStyleSup">-1</span><a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;7 &#40;0&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&#46;9 &#40;1&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;5 &#40;0&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">130&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">5&#46;00&#44; 3&#46;12-8&#46;31&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Baseline PetCO<span class="elsevierStyleInf">2</span> &#40;kPa&#41;<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;4 &#40;0&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;2 &#40;0&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;4 &#40;0&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;017&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&#46;21&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;52&#44; 0&#46;30-0&#46;89&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;018&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>AT PetCO<span class="elsevierStyleInf">2</span> &#40;kPa&#41;<span class="elsevierStyleSup">g&#44;</span><a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;9 &#40;0&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;3 &#40;0&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">5&#46;0 &#40;0&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">49&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;27&#44; 0&#46;17-0&#46;44&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>&#916; PetCO<span class="elsevierStyleInf">2</span> &#40;kPa&#41;<span class="elsevierStyleSup">g&#44;</span><a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;5 &#40;0&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;1 &#40;0&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;6 &#40;0&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">84&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;03&#44; 0&#46;01-0&#46;17&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="8" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="8" align="left" valign="top"><span class="elsevierStyleItalic">Score</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>HFSS<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&#46;7 &#40;1&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">7&#46;9 &#40;0&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&#46;8 &#40;0&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">51&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;33&#44; 0&#46;22-0&#46;49&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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                0 => "xTab1702751.png"
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            0 => array:3 [
              "identificador" => "tblfn0005"
              "etiqueta" => "a"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Cardiac death&#44; urgent heart transplantation or mechanical circulatory support up to 36 months of follow-up &#40;n&#61;54&#41;&#46;</p>"
            ]
            1 => array:3 [
              "identificador" => "tblfn0010"
              "etiqueta" => "b"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0010">Values expressed as mean &#40;standard deviation&#41;&#46;</p>"
            ]
            2 => array:3 [
              "identificador" => "tblfn0015"
              "etiqueta" => "c"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0015">Values expressed as n &#40;&#37;&#41;&#46;</p>"
            ]
            3 => array:3 [
              "identificador" => "tblfn0020"
              "etiqueta" => "d"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0020">Values expressed as median &#40;25th-75th percentile&#41;&#46;</p> <p class="elsevierStyleNotepara" id="npar0025"><span class="elsevierStyleSup">e&#44;f&#44;g</span>Of these&#44; only VO<span class="elsevierStyleInf">2</span> max&#44; VE&#47;VCO<span class="elsevierStyleInf">2</span> slope &#40;entire exercise&#41; and &#916; PetCO<span class="elsevierStyleInf">2</span> were entered in the multivariate model&#44; to avoid multicollinearity&#46;</p> <p class="elsevierStyleNotepara" id="npar0030">&#916; double product&#58; product of peak minus baseline heart rate and systolic blood pressure&#59; &#916; PetCO<span class="elsevierStyleInf">2</span>&#58; anaerobic threshold minus baseline end-tidal carbon dioxide partial pressure&#59; ACEi&#58; angiotensin-converting enzyme inhibitor&#59; ARB&#58; angiotensin receptor blocker&#59; AT&#58; anaerobic threshold&#59; Chi-square&#58; Wald chi-square value&#59; CI&#58; confidence interval&#59; Circulatory power&#58; product of peak oxygen consumption and systolic blood pressure&#59; CRT&#58; cardiac resynchronization therapy&#44; with or without defibrillator&#59; HFSS&#58; Heart Failure Survival Score&#59; HR&#58; heart rate&#59; HR recovery &#40;1st minute&#41;&#58; peak heart rate minus heart rate at first minute of recovery&#59; ICD&#58; implantable cardioverter-defibrillator&#59; LVEDD&#58; left ventricular end-diastolic diameter&#59; LVEF&#58; left ventricular ejection fraction&#59; MR&#58; moderate or severe mitral regurgitation&#59; NT-proBNP&#58; N-terminal pro-B-type natriuretic peptide&#59; NYHA&#58; New York Heart Association&#59; OUES&#58; oxygen uptake efficiency slope<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">16</span></a>&#59; peak oxygen pulse&#58; peak oxygen consumption&#47;heart rate ratio&#59; PetCO<span class="elsevierStyleInf">2</span>&#58; end-tidal carbon dioxide partial pressure&#59; RER&#58; respiratory exchange ratio &#40;ratio between carbon dioxide production and oxygen consumption&#41;&#59; RVSD&#58; right ventricular systolic dysfunction&#59; VO<span class="elsevierStyleInf">2</span> max&#58; peak oxygen consumption&#59; VO<span class="elsevierStyleInf">2</span> max &#40;&#37; predicted&#41;&#58; based on Wasserman and Hansen&#39;s formula&#59; VCO<span class="elsevierStyleInf">2</span>&#58; carbon dioxide production&#59; VE&#58; minute ventilation&#59; VO<span class="elsevierStyleInf">2</span>&#58; oxygen consumption&#46;</p>"
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Baseline data and univariate Cox regression analysis for predicting adverse events up to 36 months of follow-up&#46;</p>"
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        "etiqueta" => "Table 2"
        "tipo" => "MULTIMEDIATABLA"
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        "detalles" => array:1 [
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            "identificador" => "at2"
            "detalle" => "Table "
            "rol" => "short"
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                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">12 months</th><th class="td" title="table-head  " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">36 months</th><th class="td" title="table-head  " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">60 months</th></tr><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">n&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">&#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">n&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">&#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">n&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">&#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Combined endpoint<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">27&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">10&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">54&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">20&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">69&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">26&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Death&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">22&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">47&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">17&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">66&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">25&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Cardiac death&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">18&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">6&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">36&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">13&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">49&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">18&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Sudden death&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">13&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">18&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">6&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Worsening of heart failure&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">23&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">31&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">11&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Heart transplantation&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">12&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">19&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">7&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">22&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Urgent heart transplantation&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">15&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">5&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">17&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">6&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Mechanical circulatory support<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
              "imagenFichero" => array:1 [
                0 => "xTab1702752.png"
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          "notaPie" => array:2 [
            0 => array:3 [
              "identificador" => "tblfn0025"
              "etiqueta" => "a"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0035">Cardiac death&#44; urgent heart transplantation or mechanical circulatory support&#46;</p>"
            ]
            1 => array:3 [
              "identificador" => "tblfn0030"
              "etiqueta" => "b"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0040">All patients were in Interagency Registry for Mechanically Assisted Circulatory Support &#40;INTERMACS&#41; profiles 1 or 2&#46;<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">17</span></a></p>"
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Adverse events at 12&#44; 36 and 60 months of follow-up&#46;</p>"
        ]
      ]
      4 => array:8 [
        "identificador" => "tbl0015"
        "etiqueta" => "Table 3"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at3"
            "detalle" => "Table "
            "rol" => "short"
          ]
        ]
        "tabla" => array:2 [
          "tablatextoimagen" => array:1 [
            0 => array:2 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Chi-square&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Hazard ratio&#44; 95&#37; CI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">p&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">AUC&#44; 95&#37; CI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleItalic">12-month follow-up</span><a class="elsevierStyleCrossRef" href="#tblfn0035"><span class="elsevierStyleSup">a</span></a></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>VE&#47;VCO<span class="elsevierStyleInf">2</span> slope&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">47&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;14&#44; 1&#46;10-1&#46;18&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;91&#44; 0&#46;87-0&#46;95&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>LVEF&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;94&#44; 0&#46;89-0&#46;99&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;044&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;76&#44; 0&#46;68-0&#46;84&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Overall AUC&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">-&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">-&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">-&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;91&#44; 0&#46;88-0&#46;95&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleItalic">36-month follow-up</span><a class="elsevierStyleCrossRef" href="#tblfn0040"><span class="elsevierStyleSup">b</span></a></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>VE&#47;VCO<span class="elsevierStyleInf">2</span> slope&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">89&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;14&#44; 1&#46;11-1&#46;18&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;87&#44; 0&#46;81-0&#46;93&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Creatinine levels&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">5&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;23&#44; 1&#46;14-4&#46;36&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;020&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;69&#44; 0&#46;65-0&#46;74&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>LVEF&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;96&#44; 0&#46;93-0&#46;99&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;030&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;72&#44; 0&#46;65-0&#46;78&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Overall AUC&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">-&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">-&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">-&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;89&#44; 0&#46;84-0&#46;94&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleItalic">60-month follow-up</span><a class="elsevierStyleCrossRef" href="#tblfn0045"><span class="elsevierStyleSup">c</span></a></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>VE&#47;VCO<span class="elsevierStyleInf">2</span> slope&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">35&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;11&#44; 1&#46;08-1&#46;16&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;87&#44; 0&#46;81-0&#46;92&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Creatinine levels&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">7&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;25&#44; 1&#46;27-3&#46;96&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;005&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;68&#44; 0&#46;61-0&#46;75&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>&#916; PetCO<span class="elsevierStyleInf">2</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">5&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;39&#44; 0&#46;17-0&#46;89&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;024&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;84&#44; 0&#46;79-0&#46;90&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>LVEF&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;97&#44; 0&#46;94-0&#46;99&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;047&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;72&#44; 0&#46;66-0&#46;79&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Overall AUC&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">-&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">-&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">-&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;89&#44; 0&#46;84-0&#46;94&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleItalic">36-month follow-up &#40;low-risk&#41;</span><a class="elsevierStyleCrossRef" href="#tblfn0050"><span class="elsevierStyleSup">d</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#tblfn0055"><span class="elsevierStyleSup">e</span></a></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Sodium levels&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">18&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;79&#44; 0&#46;71-0&#46;88&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;73&#44; 0&#46;61-0&#46;85&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Creatinine levels&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">5&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;75&#44; 1&#46;20-6&#46;29&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;017&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;71&#44; 0&#46;62-0&#46;81&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>LVEF&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">5&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;94&#44; 0&#46;89-0&#46;99&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;018&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;72&#44; 0&#46;64-0&#46;80&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>&#916; PetCO<span class="elsevierStyleInf">2</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;30&#44; 0&#46;10-0&#46;94&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;039&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;73&#44; 0&#46;63-0&#46;84&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
              "imagenFichero" => array:1 [
                0 => "xTab1702749.png"
              ]
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          "notaPie" => array:5 [
            0 => array:3 [
              "identificador" => "tblfn0035"
              "etiqueta" => "a"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0045">C-index 0&#46;90&#44; 95&#37; CI 0&#46;86-0&#46;94&#46;</p>"
            ]
            1 => array:3 [
              "identificador" => "tblfn0040"
              "etiqueta" => "b"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0050">C-index 0&#46;88&#44; 95&#37; CI 0&#46;83-0&#46;92&#46;</p>"
            ]
            2 => array:3 [
              "identificador" => "tblfn0045"
              "etiqueta" => "c"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0055">C-index 0&#46;86&#44; 95&#37; CI 0&#46;82-0&#46;90&#46;</p>"
            ]
            3 => array:3 [
              "identificador" => "tblfn0050"
              "etiqueta" => "d"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0060">C-index 0&#46;83&#44; 95&#37; CI 0&#46;76-0&#46;91&#46;</p>"
            ]
            4 => array:3 [
              "identificador" => "tblfn0055"
              "etiqueta" => "e"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0065">Excluding patients with VE&#47;VCO<span class="elsevierStyleInf">2</span> slope &#8805;39&#46;0&#46;</p> <p class="elsevierStyleNotepara" id="npar0070">AUC for individual variables and for the overall model are presented&#44; for each follow-up time&#46;</p> <p class="elsevierStyleNotepara" id="npar0075">&#916; PetCO<span class="elsevierStyleInf">2</span>&#58; anaerobic threshold minus baseline end-tidal carbon dioxide partial pressure&#59; AUC&#58; area under the receiving operating characteristic curve&#59; Chi-square&#58; Wald chi-square value&#59; CI&#58; confidence interval&#59; LVEF&#58; left ventricular ejection fraction&#59; VCO<span class="elsevierStyleInf">2</span>&#58; carbon dioxide production&#59; VE&#58; minute ventilation&#46;</p>"
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Multivariate Cox regression&#46;</p>"
        ]
      ]
      5 => array:8 [
        "identificador" => "tbl0020"
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Article information

ISSN: 21742049
Original language: English

DOI:10.1016/j.repce.2017.06.017

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Year/Month	Html	Pdf	Total

2024 November	8	6	14
2024 October	31	25	56
2024 September	51	34	85
2024 August	47	39	86
2024 July	36	34	70
2024 June	26	22	48
2024 May	28	28	56
2024 April	27	30	57
2024 March	39	22	61
2024 February	27	21	48
2024 January	26	19	45
2023 December	29	21	50
2023 November	40	19	59
2023 October	34	13	47
2023 September	34	18	52
2023 August	26	21	47
2023 July	34	16	50
2023 June	20	13	33
2023 May	39	13	52
2023 April	18	3	21
2023 March	65	19	84
2023 February	57	17	74
2023 January	24	10	34
2022 December	51	22	73
2022 November	69	23	92
2022 October	36	23	59
2022 September	41	31	72
2022 August	22	23	45
2022 July	27	36	63
2022 June	34	25	59
2022 May	20	34	54
2022 April	25	21	46
2022 March	26	38	64
2022 February	25	32	57
2022 January	29	23	52
2021 December	22	32	54
2021 November	27	30	57
2021 October	30	32	62
2021 September	25	33	58
2021 August	25	32	57
2021 July	31	30	61
2021 June	29	17	46
2021 May	53	45	98
2021 April	75	116	191
2021 March	43	18	61
2021 February	43	24	67
2021 January	32	26	58
2020 December	47	21	68
2020 November	33	25	58
2020 October	29	15	44
2020 September	35	14	49
2020 August	19	14	33
2020 July	35	11	46
2020 June	33	15	48
2020 May	38	5	43
2020 April	49	7	56
2020 March	37	10	47
2020 February	63	21	84
2020 January	42	7	49
2019 December	33	5	38
2019 November	30	13	43
2019 October	42	5	47
2019 September	29	12	41
2019 August	13	9	22
2019 July	33	4	37
2019 June	37	16	53
2019 May	33	10	43
2019 April	31	21	52
2019 March	104	11	115
2019 February	123	6	129
2019 January	80	11	91
2018 December	45	9	54
2018 November	84	16	100
2018 October	148	12	160
2018 September	23	8	31
2018 August	25	7	32
2018 July	18	2	20
2018 June	31	5	36
2018 May	24	6	30
2018 April	80	14	94
2018 March	49	11	60

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