The relationship between 24-hour ambulatory blood pressure load and neutrophil-to-lymphocyte ratio | Revista Portuguesa de Cardiologia (English edition)

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BP: blood pressure; NLR: neutrophil-to-lymphocyte ratio." ] ] ] "textoCompleto" => "IntroductionHypertension (HTN) is a common condition that results in damage to important target organs including the heart, kidney and brain.<a class="elsevierStyleCrossRefs" href="#bib0215">1,2</a> Low-grade inflammation has a key role in its pathogenesis and progression.<a class="elsevierStyleCrossRef" href="#bib0225">3</a> Inflammatory processes are assumed to have particularly significant involvement in vascular remodeling of resistance arteries.<a class="elsevierStyleCrossRef" href="#bib0230">4</a> Increasing blood pressure (BP) may progressively cause a pro-inflammatory response and thus establish a vicious cycle. Furthermore, HTN is a significant risk factor in inflammatory conditions such as atherosclerosis.<a class="elsevierStyleCrossRef" href="#bib0235">5</a>The relationship between various cardiovascular conditions and inflammation has been investigated in previous studies.<a class="elsevierStyleCrossRef" href="#bib0240">6</a> Elevated C-reactive protein (CRP), vascular (VCAM-1) and intercellular (ICAM-1) adhesion molecules, monocyte chemoattractant protein-1 (MCP) and plasminogen activator inhibitor-1 (PAI-1) are some of the inflammatory molecules that are increased in HTN.<a class="elsevierStyleCrossRefs" href="#bib0245">7,8</a> Along with these well-known inflammatory markers, recent studies have shown the neutrophil-to-lymphocyte ratio (NLR) to be a reliable marker of systemic inflammation.<a class="elsevierStyleCrossRef" href="#bib0255">9</a> It has been shown to have prognostic significance in various conditions such as coronary artery disease,<a class="elsevierStyleCrossRefs" href="#bib0260">10,11</a> malignancy,<a class="elsevierStyleCrossRef" href="#bib0270">12</a> heart failure,<a class="elsevierStyleCrossRef" href="#bib0275">13</a> and cerebral and peripheral artery disease.<a class="elsevierStyleCrossRefs" href="#bib0280">14,15</a> Since HTN is considered a significant risk factor in most of these conditions, the relationship between NLR and HTN has also been thoroughly investigated.<a class="elsevierStyleCrossRef" href="#bib0290">16</a> NLR is a good predictor in high-risk conditions such as resistant HTN and non-dipper HTN.<a class="elsevierStyleCrossRefs" href="#bib0295">17,18</a>Ambulatory blood pressure monitoring (ABPM) is an important tool that is frequently used by clinicians in daily practice to guide treatment and help to identify conditions such as white-coat and masked HTN.<a class="elsevierStyleCrossRef" href="#bib0305">19</a> It is known that ABPM is a better predictor of target organ damage and cardiovascular endpoints than office BP.<a class="elsevierStyleCrossRef" href="#bib0310">20</a> However, it may have limitations in patients with ‘high-normal’ BP.<a class="elsevierStyleCrossRef" href="#bib0315">21</a> In view of this limitation, some authors suggest that BP load, defined as the percentage of abnormally elevated BP readings, is a better predictor.<a class="elsevierStyleCrossRefs" href="#bib0320">22,23</a>As far as we know, there are few data on the evaluation of severity of the inflammatory response in HTN using NLR, which is a simple and inexpensive method. Thus, in our study we aimed to evaluate the relationship between HTN severity and NLR using averaged ambulatory BP readings and BP load.MethodsStudy populationThis cross-sectional study included 300 consecutive patients with newly diagnosed essential hypertension by 24-hour ABPM using a validated device between December 2014 and December 2015. All patients had untreated essential HTN, defined as office BP of ≥140/90 mmHg (the mean of ≥2 valid readings measured on at least two visits). Patients with the following criteria were excluded from the study: current use of antihypertensive drugs, acute or chronic infectious conditions, leukocytosis (white blood cell count >12.0×103/mm3), history of malignancy, chronic renal disease (estimated glomerular filtration rate <60 ml/min/1.73 m2), elevated hepatic enzymes (bilirubin >2 upper limit of normal [ULN] or AST/ALT/ALP >3 ULN), diagnosis of secondary hypertension or white coat hypertension, moderate to severe valvular disease, symptomatic cardiac failure or prosthetic valve, history of coronary artery disease, peripheral artery disease or stroke, atrial fibrillation, thromboembolic disorders, history of hematological disease and consumption of drugs that may affect NLR.Demographic, clinical, and laboratory parameters including age, gender, diabetes, hyperlipidemia, smoking status, body mass index (BMI), fasting blood glucose level, serum creatinine level, fasting lipid profile, and complete blood count parameters were recorded in all patients.Informed consent was obtained from each patient before enrollment. The study was approved by the institutional ethics committee and performed in accordance with the Helsinki Declaration.Laboratory testsA complete blood count analysis was performed using an LH series analyzer (Beckman Coulter Inc., Hialeah, FL). NLR was calculated as the ratio of neutrophil count to lymphocyte count in admission samples. Biochemistry analysis was performed using standard tests on samples obtained in fasting conditions.All transthoracic echocardiography examinations were performed using a Philips iE33 xMATRIX system with a 2.5/3.5 MHz transducer (Philips Electronics, The Netherlands) by an experienced echocardiographer who was blinded to the patients included in the study. Left ventricular ejection fraction (LVEF) and left ventricular mass index (LVMI) were calculated as recommended by the current guidelines.<a class="elsevierStyleCrossRef" href="#bib0330">24</a> An electrocardiogram was obtained for all patients.Blood pressure measurementTwenty-four-hour ABPM readings (Oscar 2 oscillometric monitor, SunTech Medical Inc., Morrisville, NC) were assessed for all patients. Appropriate cuff sizes were selected by trained nurses. Measurements were taken at 15-min intervals during the day and at 30-min intervals at night. Patients with fewer than 80% valid measurements were excluded. Patients with mean 24-hour systolic BP (SBP) ≥130 mmHg and/or diastolic BP (DBP) ≥80 mmHg or mean daytime SBP ≥135 mmHg and/or DBP ≥85 mmHg were diagnosed as hypertensive.<a class="elsevierStyleCrossRef" href="#bib0305">19</a> A non-dipper pattern was defined as a decrease of <10% in SBP between daytime (7:00 am to 11:00 pm) and nighttime (11:00 pm to 7:00 am). Mean 24-hour, daytime, and nighttime SBP and DBP were calculated for each patient using the hourly averages of ambulatory BP recordings. BP load and BP variability were recorded as additional data. BP load was defined as the percentage of values reaching or exceeding 135 mmHg SBP or 85 mmHg DBP daytime and 120 mmHg SBP or 70 mmHg DBP nighttime on 24-hour BP readings. 24-hour BP load was also calculated based on these cut-off values. For a more reliable evaluation of BP variability, we also performed an additional analysis using the weighted mean of daytime and nighttime standard deviation for both SBP and DBP, as previously described.<a class="elsevierStyleCrossRef" href="#bib0335">25</a>Statistical analysisStatistical analyses were performed using SPSS software (version 21.0; SPSS, Chicago, IL). Continuous data were presented as medians with interquartile range or mean ± SD for non-normally and normally distributed variables, respectively. The Shapiro-Wilk test was used to test the distribution pattern and logarithmic conversion was performed for non-normally distributed variables. The study population was categorized into quartiles based on NLR levels. Comparisons between groups were carried out by Kruskal-Wallis tests or analysis of variance, as appropriate. Differences between groups were revealed using Dunn's procedure for data without normal distribution and Bonferroni's multiple comparison post hoc test for data with normal distribution. Categorical variables were summarized as percentages and compared with the chi-square test. Correlations between variables were investigated by the Pearson correlation coefficient. Age, gender, diabetes, hyperlipidemia, smoking status, BMI, serum creatinine, hemoglobin, fasting glucose, white blood cell count, platelet count, log NLR, total cholesterol, low-density lipoprotein, high-density lipoprotein cholesterol, triglycerides, aspirin medication, LVEF and LVMI were tested by univariate linear regression analysis. Multivariate regression analysis including all univariate correlates (p<0.1) was used to identify predictors for 24-hour systolic and diastolic BP and BP load. For all tests, statistical significance was accepted as a p value <0.05.ResultsThree hundred hypertensive patients (47% male) were evaluated. The mean age of the population was 48.5±14 years. Patients were divided into quartiles according to NLR values (first: <1.55; second: 1.55-1.92; third: 1.92-2.48; and fourth: >2.48). There were no differences between quartiles in terms of basal demographics, cardiovascular risk factors or echocardiographic parameters (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>). Baseline laboratory findings are presented in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>. Fasting blood glucose, serum creatinine, hemoglobin, platelet count, and lipid profile were not different across NLR quartiles. White blood cell and neutrophil counts were significantly higher in upper quartiles of NLR. There was also a statistically significant trend towards lower lymphocyte count in patients in the fourth quartile.<elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia>Patients’ ABPM data are shown in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>. In the interquartile evaluation, daytime SBP, 24-hour DBP, daytime DBP, daytime SBP load, 24-hour DBP load and daytime DBP load were found to be significantly higher in the upper two quartiles (p<0.05 for all). The difference was more noticeable in DBP data. Dipping status and BP variability data were not significantly different between quartiles (p>0.05).<elsevierMultimedia ident="tbl0015"></elsevierMultimedia>Subsequently, the relationship between mean BP and BP load values and NLR was evaluated. A positive correlation between log NLR and daytime, nighttime and 24-hour BP and BP load values was identified (p<0.05 for all). Correlations of 24-hour systolic BP (r=0.194; 95% confidence interval [CI]: 0.074-0.320, p=0.001) and 24-hour diastolic BP (r=0.197; 95% CI: 0.076-0.307, p=0.001), 24-hour systolic BP load (r=0.157; 95% CI: 0.032-0.278, p=0.006) and 24-hour diastolic BP load (r=0.181; 95% CI: 0.054-0.295, p=0.002) with log NLR are shown in <a class="elsevierStyleCrossRef" href="#fig0005">Figure 1</a>. Additionally, daytime SBP load (r=0.150, 95% CI: 0.025-0.265, p=0.009), nighttime SBP load (r=0.129, 95% CI: 0.011-0.247, p=0.026), daytime DBP load (r=0.160, 95% CI: 0.040-0.273, p=0.005) and nighttime DBP load (r=0.173, 95% CI: 0.049-0.289, p=0.003) were positively correlated with log NLR. Similarly, a significant positive correlation was observed between mean daytime SBP (r=0.173, 95% CI: 0.055-0.292, p=0.003), nighttime SBP (r=0.206, 95% CI: 0.091-0.332, p< 0.001), daytime DBP (r=0.170, 95% CI: 0.059-0.282, p=0.003) and nighttime DBP (r=0.214, 95% CI: 0.096-0.331, p<0.001) and log NLR values.<elsevierMultimedia ident="fig0005"></elsevierMultimedia>After construction of multiple linear regression models with the four ABPM components associated with log NLR levels as independent variables, log NLR values maintained an independent association with 24-hour SBP, 24-hour DBP, 24-hour SBP load (<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>) and 24-hour DBP load (<a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>). When 24-hour SBP was taken as a continuous variable, multivariate linear regression analysis revealed that 24-hour SBP was correlated with fasting blood glucose (β=0.160, 95% CI: 0.016-0.088, p=0.005), female gender (β=-0.114, 95% CI: -5.409-0.078, p=0.044), LVMI (β=0.194, 95% CI: 0.049-0.191, p=0.001) and log NLR (β=0.208 95% CI: 7.881-23.975, p<0.001). Similarly, multivariate linear regression analysis demonstrated significant associations between age (β=-0.197, 95% CI: -0.197-0.047, p=0.002), LVEF (β=-0.162, 95% CI: -0.837-0.149, p=0.005), log NLR (β=0.216, 95% CI: 6.119-18.741, p<0.001) and 24-hour DBP.<elsevierMultimedia ident="tbl0020"></elsevierMultimedia><elsevierMultimedia ident="tbl0025"></elsevierMultimedia>DiscussionThe results of our study show that in patients with untreated HTN, admission NLR values and ambulatory BP and BP load measurements were correlated. To our knowledge, this is the first study in the literature demonstrating such a correlation between NLR and BP severity.Elevated NLR values are a predictor of high cardiovascular risk<a class="elsevierStyleCrossRef" href="#bib0340">26</a> and are correlated with inflammatory activity and the severity of numerous diseases.<a class="elsevierStyleCrossRefs" href="#bib0345">27,28</a> Increased renin-angiotensin-aldosterone system activity and CRP-mediated inflammation are involved in the inflammatory response observed in hypertensive patients, and activation of peroxisome proliferator-activated receptors may protect against these effects.<a class="elsevierStyleCrossRef" href="#bib0230">4</a> Angiotensin II triggers a series of inflammatory processes resulting in vascular remodeling and injury via endothelin-1 and NAD(P)H oxidase.<a class="elsevierStyleCrossRef" href="#bib0355">29</a> Other than the vascular remodeling resulting from chronic HTN, there is no other evidence indicating whether low-grade inflammation level is reflected in short-term BP values. However, structural vascular alterations occurring during chronic HTN, along with some functional mechanisms, may cause acute BP alterations and inflammation.<a class="elsevierStyleCrossRef" href="#bib0360">30</a> In previous studies it was shown that high-sensitivity CRP and leukocyte count were elevated in patients experiencing acute BP increase in conditions such as hypertensive crisis.<a class="elsevierStyleCrossRef" href="#bib0365">31</a> Shear stress due to high BP levels may lead to an increase in inflammation in the short term by increased expression of adhesion molecules, endothelial dysfunction and NO-related mechanisms.<a class="elsevierStyleCrossRef" href="#bib0370">32</a> It is known that ICAM-1 and interleukin-6 increase with increasing BP.<a class="elsevierStyleCrossRef" href="#bib0375">33</a> In our study also, patients with higher NLR were found to have higher ambulatory BP measurements, particularly for DBP. Like mean BP values, the relationship of BP load with higher NLR values suggests that the inflammation observed in these patients is associated with short-term barotrauma. A higher BP load means that target organs are exposed to higher pressure for a longer duration, even if mean BP is normal. Additionally, patients with increased BP load are subject to overloading of the cardiovascular system, with consequent negative impact on related structures. Higher BP load may promote an inflammatory response to HTN. Recent studies reporting an association between BP load and target organ damage have shown that this relationship is not independent of 24-hour BP levels.<a class="elsevierStyleCrossRef" href="#bib0380">34</a> On the contrary, Wang et al. have shown that BP load is an independent predictor of target organ damage in patients with chronic renal disease.<a class="elsevierStyleCrossRef" href="#bib0325">23</a> Higher BP load (‘baric impact’) may cause endothelial dysfunction associated with vasopressor effects and thus may increase inflammation.<a class="elsevierStyleCrossRef" href="#bib0385">35</a>As a probable predictor of BP severity, NLR has been the subject of antihypertensive therapy studies. Antihypertensive drugs may lead to a decrease in NLR, by both BP-lowering and anti-inflammatory effects.<a class="elsevierStyleCrossRefs" href="#bib0390">36,37</a> In previous studies non-dipping status and increased BP variability were associated with higher NLR.<a class="elsevierStyleCrossRefs" href="#bib0400">38,39</a> In our study, the lack of difference in BP variability and non-dipper status between groups made the relationship between NLR and BP/BP load clearer. Furthermore, increased pulse pressure is considered a significant marker of chronic inflammation and arterial stiffness.<a class="elsevierStyleCrossRef" href="#bib0410">40</a> In a smaller cohort including normotensives NLR was reportedly correlated with 24-hour SBP and night-time SBP.<a class="elsevierStyleCrossRef" href="#bib0415">41</a> In the same study, pulse pressure was also correlated positively with NLR. In our study, mean pulse pressure did not differ between quartiles and therefore did not contribute significantly to the results. Interestingly, Gang and Yanyan showed that NLR was increased in patients suffering from HTN with hyperhomocysteinemia and was positively correlated with homocysteine levels but not with BP.<a class="elsevierStyleCrossRef" href="#bib0420">42</a> In their study, they also found no difference in NLR values between hypertensive and normotensive groups. A single office BP measurement and lack of data on antihypertensive medication could be responsible for their results.In the present study, we found a weak correlation between ABPM data and log NLR values. There are several possible reasons for this: 24-hour ABPM provides short-term data and has limited reproducibility, which makes it difficult to clarify the severity of HTN. In addition, the selection of a relatively low-risk cohort of hypertensive patients may have meant they had only a low-grade inflammatory response, which might have weakened the correlation between NLR and severity of HTN. Nevertheless, despite other confounding factors such as the unknown chronicity of HTN and underlying subclinical end-organ damage, the available data suggest that higher NLR is associated with higher BP and BP load. Thus, our study may function as a hypothesis-generating study and lead to further research.Our study has some limitations. Firstly, its cross-sectional design precludes drawing conclusions about causal relationships between NLR values and short-term ABPM results. Since ABPM was performed only once in each patient, the reproducibility of ambulatory BP measurements is another limitation. We think that the use of BP load as an outcome is also a limitation because its importance in cardiovascular risk stratification is debatable. In addition, it would have been better to have evaluated leukocyte activation markers, pro-inflammatory cytokines and oxidative stress markers. Exclusion of patients with severe complications of HTN from the present study prevents us from generalizing our results to the whole hypertensive patient population.ConclusionsWe showed for the first time a significant correlation between high BP load and NLR. Further large-scale studies are needed to assess whether NLR can be used to predict HTN severity and to guide therapy in patients with HTN.Ethical disclosuresProtection of human and animal subjectsThe authors declare that no experiments were performed on humans or animals for this study.Confidentiality of dataThe authors declare that they have followed the protocols of their work center on the publication of patient data.Right to privacy and informed consentThe authors declare that no patient data appear in this article.Conflicts of interestThe authors have no conflicts of interest to declare." "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres805493" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction and Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec803630" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres805494" "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" => "Conclusão" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec803629" "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" => "Study population" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Laboratory tests" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Blood pressure measurement" ] 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:3 [ "identificador" => "sec0050" "titulo" => "Ethical disclosures" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0055" "titulo" => "Protection of human and animal subjects" ] 1 => array:2 [ "identificador" => "sec0060" "titulo" => "Confidentiality of data" ] 2 => array:2 [ "identificador" => "sec0065" "titulo" => "Right to privacy and informed consent" ] ] ] 10 => array:2 [ "identificador" => "sec0070" "titulo" => "Conflicts of interest" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2016-05-11" "fechaAceptado" => "2016-07-15" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec803630" "palabras" => array:4 [ 0 => "Ambulatory blood pressure" 1 => "Neutrophil-to-lymphocyte ratio" 2 => "Hypertension" 3 => "Inflammation" ] ] ] "pt" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palavras-chave" "identificador" => "xpalclavsec803629" "palabras" => array:4 [ 0 => "Pressão arterial em ambulatório" 1 => "Proporção neutrófilos/linfócitos" 2 => "Hipertensão" 3 => "Inflamação" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "Introduction and ObjectiveThe neutrophil-to-lymphocyte ratio (NLR) is established as a reliable marker of systemic inflammation. Low-grade inflammation has a key role in the pathogenesis and progression of hypertension (HTN). Blood pressure (BP) load, defined as the percentage of abnormally elevated BP readings, is a good marker of HTN severity. We aimed to evaluate the relationship between HTN severity and NLR using averaged ambulatory BP readings and BP load. MethodsA total of 300 patients with untreated essential HTN were included in this cross-sectional study. Patients were divided into quartiles according to NLR values (first: <1.55; second: 1.55-1.92; third: 1.92-2.48; and fourth: >2.48). Averaged ambulatory BP values and BP load were assessed for each quartile. ResultsIn the interquartile evaluation there were no differences between quartiles in terms of baseline demographic, clinical and echocardiographic characteristics (p>0.05). Daytime systolic BP (SBP), 24-hour diastolic BP (DBP), daytime DBP, daytime SBP load, 24-hour DBP load and daytime DBP load were found to be significantly higher in the upper two quartiles (p<0.05 for all). In correlation analysis, log NLR values were found to be positively correlated with 24-hour SBP, DBP, SBP load and DBP load (Pearson coefficients of 0.194, 0.197, 0.157 and 0.181, respectively; p<0.01 for all). In multivariate analysis, log NLR had an independent association with 24-hour SBP and DBP and 24-hour SBP and DBP load. ConclusionThis study showed for the first time that increased NLR is independently associated with HTN severity in untreated essential HTN patients." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction and Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] "pt" => array:3 [ "titulo" => "Resumo" "resumen" => "Introdução e objetivosA relação neutrófilos/linfócitos (RNL) foi estabelecida como um marcador inflamatório sistémico fiável. Uma inflamação de baixo grau tem um papel fundamental na patogénese e na progressão da hipertensão (HT). A carga da pressão arterial (PA) definida como a percentagem de leituras da PA anormalmente elevadas é um bom marcador da gravidade da PA. O objetivo deste estudo é avaliar a relação entre a gravidade da PA e a RNL pela utilização da média de leituras ambulatórias da PA e da carga da PA. MétodosUm total de 300 doentes, com HT essencial não tratada, foram incluídos neste estudo transversal. Os doentes foram divididos em quartis, de acordo com os valores da RNL (primeiro <1,55; segundo 1,55-1,92; terceiro 1,92-2,48 e o quarto > 2,48). Os valores médios da PA em ambulatório e a carga da PA foram avaliados para cada quartil. ResultadosNa avaliação interquartis, não houve diferença entre quartis nas características demográficas, clínicas e ecocardiográficas basais (p > 0,05). A PA sistólica diurna (PAS), a PA diastólica (PAD) a 24 horas, a PAD diurna, a carga da PAS diurna, a PAD a 24 horas e a PAD diurna foram significativamente mais elevadas nos dois quartis superiores (p < 0,05 para todos). Na análise de correlação, os valores do logaritmo de RNL foram positivamente correlacionados com a PAS a 24 horas, com a PAD, com a PAS carga e com a PAD carga (coeficientes de Pearson de 0,194, 0,197, 0,157 e 0,181, respetivamente; p<0,01 para todos). Na análise multivariada, os valores do logaritmo da RNL mostraram uma associação independente com a PAS-PAD a 24 horas e com a carga da PAS-PAD a 24 horas. ConclusãoEste estudo mostrou pela primeira vez que o aumento da RNL está independentemente associado à gravidade da PA nos doentes com HT essencial não tratada." "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" => "Conclusão" ] ] ] ] "multimedia" => array:6 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 2676 "Ancho" => 3350 "Tamanyo" => 769304 ] ] "descripcion" => array:1 [ "en" => "Pearson's correlation analysis demonstrating correlations between NLR and (A) 24-hour systolic BP; (B) 24-hour systolic BP load; (C) 24-hour diastolic BP; and (D) 24-hour diastolic BP load. BP: blood pressure; NLR: neutrophil-to-lymphocyte ratio." ] ] 1 => 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:3 [ "leyenda" => "BMI: body mass index; IVS: interventricular septum; LVEDD: left ventricular end-diastolic diameter; LVEF: left ventricular ejection fraction; LVMI: left ventricular mass index; NLR: neutrophil-to-lymphocyte ratio. Data are expressed as mean ± standard deviation, median with interquartile range, or percentage frequency, as appropriate. NLR quartiles: first: 0.74-1.55; second: 1.55-1.92; third: 1.92-2.48; fourth: 2.48-6.64." "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">All (n=300) \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">1st quartile (n=75) \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">2nd quartile (n=75) \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">3rd quartile (n=75) \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">4th quartile (n=75) \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<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> \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">Age, years \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">48.5±14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">47.7±14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">48.5±13 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">47.7±15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">49.9±14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.776 \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, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">141 (47) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37 (49) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40 (53) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">32 (43) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">32 (43) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.457 \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">BMI, kg/m2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22.4 (21.1-23.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22.8 (21.3-23.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22.1 (20.9-23.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22.3 (21.1-23.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22.1 (21.1-23.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.543 \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, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">41 (14) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7 (9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12 (16) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9 (12) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13 (17) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.479 \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">Hyperlipidemia, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">21 (7) \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">8 (11) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8 (11) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4 (5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.071 \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">Smoking, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">36 (12) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8 (11) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12 (16) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11 (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">0.290 \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">Aspirin therapy, n (%) \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="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">0 \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">2 (3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.568 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="7" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="7" align="left" valign="top">Echocardiographic characteristics</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">IVS, mm \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.4±1.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.2±1.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.5±1.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.2±1.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.5±1.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.578 \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">Posterior wall, mm \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.9±1.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.7±1.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.0±1.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.8±1.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.9±1.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.666 \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">LVEDD, mm \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">46.1±3.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">46.4±3.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">45.8±2.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">46.2±3.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">46.2±3.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.822 \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">61.9±2.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">61.7±3.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">62.1±2.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">61.6±3.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">62.3± 3.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.494 \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">LVMI, g/m2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">93.3±19.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">92.6±19.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">94.0±19.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">92.3±18.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">94.3±20.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.897 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1351722.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "Comparison between groups." ] ] ] "descripcion" => array:1 [ "en" => "Baseline characteristics of patients by neutrophil-to-lymphocyte ratio quartiles." ] ] 2 => 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:3 [ "leyenda" => "HDL: high-density lipoprotein; LDL: low-density lipoprotein; NLR: neutrophil-to-lymphocyte ratio; WBC: white blood cell count. Data are expressed as mean ± standard deviation or median with interquartile range, as appropriate. NLR quartiles: first: 0.74-1.55; second: 1.55-1.92; third: 1.92-2.48; fourth: 2.48-6.64." "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">All (n=300) \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">1st quartile (n=75) \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">2nd quartile (n=75) \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">3rd quartile (n=75) \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">4th quartile (n=75) \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<a class="elsevierStyleCrossRef" href="#tblfn0010">a</a> \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">Fasting blood glucose, mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">90 (81-102) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">89 (81-99) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">90 (82-104) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">90 (82-99) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">91 (81-106) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.914 \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">Serum creatinine, mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.85 (0.72-1.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.83 (0.70-1.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.86 (0.74-0.97) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.81 (0.70-0.98) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.88 (0.73-1.03) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.679 \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">Hemoglobin, g/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">14.3±1.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">14.4±1.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">14.4±1.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">14.4±1.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">14.1±1.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.374 \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">WBC, 103/mm3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7.8±1.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">6.8±1.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7.8±1.4<a class="elsevierStyleCrossRef" href="#tblfn0020">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7.9±1.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">8.6±2.0<a class="elsevierStyleCrossRef" href="#tblfn0015">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \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">Neutrophils, 103/mm3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4.7±1.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.4±0.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4.3±0.7<a class="elsevierStyleCrossRef" href="#tblfn0025">d</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4.9±1.0<a class="elsevierStyleCrossRef" href="#tblfn0015">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">5.9±1.5<a class="elsevierStyleCrossRef" href="#tblfn0025">d</a> \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">Lymphocytes, 103/mm3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.3±0.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.7±0.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.5±0.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.2±0.4<a class="elsevierStyleCrossRef" href="#tblfn0020">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.9±0.4<a class="elsevierStyleCrossRef" href="#tblfn0025">d</a> \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">NLR \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.09±0.83 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.27±0.18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.71±0.10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.19±0.16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.2±0.80 \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></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Platelets, 103/mm3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">265±67 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">251±64 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">263±62 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">269±64 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">279±75 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.075 \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">Total cholesterol, mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">202±40 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">205±34 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">206±38 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">201±45 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">198±43 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.582 \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">HDL cholesterol, mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">46 (40-54) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">45 (40-56) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">47 (40-55) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">46 (39-55) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">45 (40-51) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.540 \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">LDL cholesterol, mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">143±35 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">144±32 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">148±35 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">142±37 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">140±35 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.611 \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">Triglycerides, mg/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">143 (94-215) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">145 (90-214) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">159 (102-217) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">135 (91-224) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">126 (91-183) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.247 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1351718.png" ] ] ] "notaPie" => array:4 [ 0 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "a" "nota" => "Comparison between groups." ] 1 => array:3 [ "identificador" => "tblfn0015" "etiqueta" => "b" "nota" => "p<0.05 compared with the previous quartile." ] 2 => array:3 [ "identificador" => "tblfn0020" "etiqueta" => "c" "nota" => "p<0.01 compared with the previous quartile." ] 3 => array:3 [ "identificador" => "tblfn0025" "etiqueta" => "d" "nota" => "p<0.001 compared with the previous quartile." ] ] ] "descripcion" => array:1 [ "en" => "Laboratory parameters of patients by neutrophil-to-lymphocyte ratio quartiles." ] ] 3 => 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:3 [ "leyenda" => "DBP: diastolic blood pressure; NLR: neutrophil-to-lymphocyte ratio; SBP: systolic blood pressure; SD: standard deviation; wSD: weighted standard deviation. Data are expressed as mean ± standard deviation (SD), median with interquartile range, or percentage frequency, as appropriate. Bold values indicate statistical significance. NLR quartiles: first: 0.74-1.55; second: 1.55-1.92; third: 1.92-2.48; fourth: 2.48-6.64." "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">All (n=300) \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">1st quartile (n=75) \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">2nd quartile (n=75) \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">3rd quartile (n=75) \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">4th quartile (n=75) \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<a class="elsevierStyleCrossRef" href="#tblfn0030">a</a> \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">24-h SBP, mmHg \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">139.7±12.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">137.0±11.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">139.0±10.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">140.4±11.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">142.2±14.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.09 \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">Daytime SBP, mmHg \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">142.4±11.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">139.7±10.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">141.5±11.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">143.5±11.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">144.7±13.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.048 \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">Nighttime SBP, mmHg \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">127 (118-137) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">126 (117-135) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">125 (118-133) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">127 (118-139) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">132 (117-140) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.295 \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">24-h DBP, mmHg \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">83.6±9.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">80.7±8.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">83.0±8.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">84.6±8.6<a class="elsevierStyleCrossRef" href="#tblfn0035">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">85.8±9.5<a class="elsevierStyleCrossRef" href="#tblfn0040">c</a> \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-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Daytime DBP, mmHg \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">85.7±9.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">82.8±8.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">84.9±8.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">87.1±8.7<a class="elsevierStyleCrossRef" href="#tblfn0040">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">87.9±9.5<a class="elsevierStyleCrossRef" href="#tblfn0040">c</a> \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">Nighttime DBP, mmHg \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">74 (68-82) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">71 (63-80) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">73 (68-80) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">74 (68-82) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">77 (70-85) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.059 \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">Non-dippers, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">151 (51) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40 (54) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">30 (40) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37 (49) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">44 (59) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.126 \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">SD of 24-h SBP, mmHg \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15.6 (13.2-18.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15.2 (12.6-18.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">16.1 (14.4-18.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15.1 (12.4-18.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15.8 (13.0-18.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.170 \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">SD of 24-h DBP, mmHg \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.4 (9.5-13.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.2 (9.2-13.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.9 (10.6-14.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.1 (9.3-13.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.1 (9.1-14.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.374 \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">wSD of SBP \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.9 (11.7-16.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.4 (11.5-15.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.8 (13.0-16.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.2 (11.6-17.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.1 (11.5-15.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.152 \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">wSD of DBP \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.2 (8.6-12.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.9 (8.1-11.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.4 (9.1-12.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.1 (8.6-12.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.0 (8.3-12.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.469 \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">24-h pulse pressure \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">56.1±9.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">56.3±9.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">55.8±9.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">56.0±8.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">56.4±9.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.993 \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">24-h SBP load, (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">60.2±23.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">54.8±23.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">58.8±21.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">63.2±22.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">63.8±25.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.084 \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">Daytime SBP load, (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">59.1±24.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">53.3±23.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">57.4±22.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">62.9±23.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">62.6±26.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.045 \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">Nighttime SBP load, (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">71 (43-100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">57 (32-90) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">71 (43-86) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">71 (43-100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">83 (43-100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.454 \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">24-h DBP load, (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">50.9±26.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42.2±26.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">48.6±23.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">55.8±26.5<a class="elsevierStyleCrossRef" href="#tblfn0040">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">56.8±26.2<a class="elsevierStyleCrossRef" href="#tblfn0040">c</a> \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">Daytime DBP load, (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">48.4±27.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">39.5±26.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">45.6±25.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">54.5±28.3<a class="elsevierStyleCrossRef" href="#tblfn0040">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">54.0±27.7<a class="elsevierStyleCrossRef" href="#tblfn0040">c</a> \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></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Nighttime DBP load, (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">60 (33-86) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">57 (26-86) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">57 (33-86) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">67 (43-86) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">71 (43-100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.087 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1351719.png" ] ] ] "notaPie" => array:3 [ 0 => array:3 [ "identificador" => "tblfn0030" "etiqueta" => "a" "nota" => "Comparison between groups." ] 1 => array:3 [ "identificador" => "tblfn0035" "etiqueta" => "b" "nota" => "p<0.05 compared with first quartile." ] 2 => array:3 [ "identificador" => "tblfn0040" "etiqueta" => "c" "nota" => "p<0.01 compared with first quartile." ] ] ] "descripcion" => array:1 [ "en" => "Comparison of ambulatory blood pressure monitoring data across neutrophil-to-lymphocyte ratio quartiles." ] ] 4 => 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" => "BMI: body mass index; CI: confidence interval; LVEF: left ventricular ejection fraction; LVMI: left ventricular mass index; NLR: neutrophil-to-lymphocyte ratio. Bold values indicate statistical significance." "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-with-role" title="table-head ; entry_with_role_rowhead " align="left" valign="top" scope="col">Variables \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Univariate</th><th class="td" title="table-head " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Multivariate</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">β \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">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">β \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">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-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Female \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.113 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-10.6-0.01 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.05 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.04 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-8.257-4.523 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.566 \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">Age \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.142 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.047-0.410 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.014 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.063 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.088-0.292 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.293 \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">BMI \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.102 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.179-3.431 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.077 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.097 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.188-3.266 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.08 \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">Fasting blood glucose \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.193 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.052-0.194 \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">0.153 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.024-0.170 \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></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Hemoglobin \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.096 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.274-3.357 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.096 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.121 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.199-4.077 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.075 \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">-0.104 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-1.713-0.078 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.073 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.081 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-1.517-0.238 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.153 \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">LVMI \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.241 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.156-0.423 \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">0.151 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.04-0.325 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.012 \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">Log NLR \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.157 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.643-40.293 \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">0.174 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.818-42.135 \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></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1351720.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Univariate and multivariate linear regression models for 24-hour systolic blood pressure load." ] ] 5 => array:8 [ "identificador" => "tbl0025" "etiqueta" => "Table 5" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at5" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "CI: confidence interval; HDL: high-density lipoprotein; NLR: neutrophil-to-lymphocyte ratio. Bold values indicate statistical significance." "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-with-role" title="table-head ; entry_with_role_rowhead " align="left" valign="top" scope="col">Variables \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Univariate</th><th class="td" title="table-head " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Multivariate</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">β \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">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">β \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">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-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Age \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.186 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.539-0.134 \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">-0.178 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.525-0.118 \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></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Creatinine \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.099 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.074-1.093 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.087 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.077 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.176-0.964 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.174 \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">HDL cholesterol \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.099 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.545-0.038 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.088 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.043 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">-0.402-0.179 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.451 \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">Log NLR \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.181 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.448-49.088 \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">0.177 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.09-48.214 \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></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1351721.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Univariate and multivariate linear regression models for 24-hour diastolic blood pressure load." ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:42 [ 0 => array:3 [ "identificador" => "bib0215" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Hypertension: a global perspective" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "K. 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The relationship between 24-hour ambulatory blood pressure load and neutrophil-to-lymphocyte ratio

A relação entre a carga da pressão arterial em ambulatório durante 24 horas e a proporção neutrófilos/linfócitos

Tolga Çimen, Hamza Sunman, Tolga Han Efe

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medisay@gmail.com

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, Mehmet Erat, Haluk Furkan Şahan, Engin Algül, İlkin Guliyev, Ahmet Akyel, Mehmet Doğan, Sadık Açıkel, Ekrem Yeter

Department of Cardiology, Dışkapı Yıldırım Beyazıt Training and Research Hospital, Ankara, Turkey

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          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Pearson&#39;s correlation analysis demonstrating correlations between NLR and &#40;A&#41; 24-hour systolic BP&#59; &#40;B&#41; 24-hour systolic BP load&#59; &#40;C&#41; 24-hour diastolic BP&#59; and &#40;D&#41; 24-hour diastolic BP load&#46; BP&#58; blood pressure&#59; NLR&#58; neutrophil-to-lymphocyte ratio&#46;</p>"
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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Hypertension &#40;HTN&#41; is a common condition that results in damage to important target organs including the heart&#44; kidney and brain&#46;<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">1&#44;2</span></a> Low-grade inflammation has a key role in its pathogenesis and progression&#46;<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">3</span></a> Inflammatory processes are assumed to have particularly significant involvement in vascular remodeling of resistance arteries&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">4</span></a> Increasing blood pressure &#40;BP&#41; may progressively cause a pro-inflammatory response and thus establish a vicious cycle&#46; Furthermore&#44; HTN is a significant risk factor in inflammatory conditions such as atherosclerosis&#46;<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">5</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">The relationship between various cardiovascular conditions and inflammation has been investigated in previous studies&#46;<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">6</span></a> Elevated C-reactive protein &#40;CRP&#41;&#44; vascular &#40;VCAM-1&#41; and intercellular &#40;ICAM-1&#41; adhesion molecules&#44; monocyte chemoattractant protein-1 &#40;MCP&#41; and plasminogen activator inhibitor-1 &#40;PAI-1&#41; are some of the inflammatory molecules that are increased in HTN&#46;<a class="elsevierStyleCrossRefs" href="#bib0245"><span class="elsevierStyleSup">7&#44;8</span></a> Along with these well-known inflammatory markers&#44; recent studies have shown the neutrophil-to-lymphocyte ratio &#40;NLR&#41; to be a reliable marker of systemic inflammation&#46;<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">9</span></a> It has been shown to have prognostic significance in various conditions such as coronary artery disease&#44;<a class="elsevierStyleCrossRefs" href="#bib0260"><span class="elsevierStyleSup">10&#44;11</span></a> malignancy&#44;<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">12</span></a> heart failure&#44;<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">13</span></a> and cerebral and peripheral artery disease&#46;<a class="elsevierStyleCrossRefs" href="#bib0280"><span class="elsevierStyleSup">14&#44;15</span></a> Since HTN is considered a significant risk factor in most of these conditions&#44; the relationship between NLR and HTN has also been thoroughly investigated&#46;<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">16</span></a> NLR is a good predictor in high-risk conditions such as resistant HTN and non-dipper HTN&#46;<a class="elsevierStyleCrossRefs" href="#bib0295"><span class="elsevierStyleSup">17&#44;18</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Ambulatory blood pressure monitoring &#40;ABPM&#41; is an important tool that is frequently used by clinicians in daily practice to guide treatment and help to identify conditions such as white-coat and masked HTN&#46;<a class="elsevierStyleCrossRef" href="#bib0305"><span class="elsevierStyleSup">19</span></a> It is known that ABPM is a better predictor of target organ damage and cardiovascular endpoints than office BP&#46;<a class="elsevierStyleCrossRef" href="#bib0310"><span class="elsevierStyleSup">20</span></a> However&#44; it may have limitations in patients with &#8216;high-normal&#8217; BP&#46;<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">21</span></a> In view of this limitation&#44; some authors suggest that BP load&#44; defined as the percentage of abnormally elevated BP readings&#44; is a better predictor&#46;<a class="elsevierStyleCrossRefs" href="#bib0320"><span class="elsevierStyleSup">22&#44;23</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">As far as we know&#44; there are few data on the evaluation of severity of the inflammatory response in HTN using NLR&#44; which is a simple and inexpensive method&#46; Thus&#44; in our study we aimed to evaluate the relationship between HTN severity and NLR using averaged ambulatory BP readings and BP load&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Study population</span><p id="par0025" class="elsevierStylePara elsevierViewall">This cross-sectional study included 300 consecutive patients with newly diagnosed essential hypertension by 24-hour ABPM using a validated device between December 2014 and December 2015&#46; All patients had untreated essential HTN&#44; defined as office BP of &#8805;140&#47;90 mmHg &#40;the mean of &#8805;2 valid readings measured on at least two visits&#41;&#46; Patients with the following criteria were excluded from the study&#58; current use of antihypertensive drugs&#44; acute or chronic infectious conditions&#44; leukocytosis &#40;white blood cell count &#62;12&#46;0&#215;10<span class="elsevierStyleSup">3</span>&#47;mm<span class="elsevierStyleSup">3</span>&#41;&#44; history of malignancy&#44; chronic renal disease &#40;estimated glomerular filtration rate &#60;60 ml&#47;min&#47;1&#46;73 m<span class="elsevierStyleSup">2</span>&#41;&#44; elevated hepatic enzymes &#40;bilirubin &#62;2 upper limit of normal &#91;ULN&#93; or AST&#47;ALT&#47;ALP &#62;3 ULN&#41;&#44; diagnosis of secondary hypertension or white coat hypertension&#44; moderate to severe valvular disease&#44; symptomatic cardiac failure or prosthetic valve&#44; history of coronary artery disease&#44; peripheral artery disease or stroke&#44; atrial fibrillation&#44; thromboembolic disorders&#44; history of hematological disease and consumption of drugs that may affect NLR&#46;</p><p id="par0030" class="elsevierStylePara elsevierViewall">Demographic&#44; clinical&#44; and laboratory parameters including age&#44; gender&#44; diabetes&#44; hyperlipidemia&#44; smoking status&#44; body mass index &#40;BMI&#41;&#44; fasting blood glucose level&#44; serum creatinine level&#44; fasting lipid profile&#44; and complete blood count parameters were recorded in all patients&#46;</p><p id="par0035" class="elsevierStylePara elsevierViewall">Informed consent was obtained from each patient before enrollment&#46; The study was approved by the institutional ethics committee and performed in accordance with the Helsinki Declaration&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Laboratory tests</span><p id="par0040" class="elsevierStylePara elsevierViewall">A complete blood count analysis was performed using an LH series analyzer &#40;Beckman Coulter Inc&#46;&#44; Hialeah&#44; FL&#41;&#46; NLR was calculated as the ratio of neutrophil count to lymphocyte count in admission samples&#46; Biochemistry analysis was performed using standard tests on samples obtained in fasting conditions&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">All transthoracic echocardiography examinations were performed using a Philips iE33 xMATRIX system with a 2&#46;5&#47;3&#46;5 MHz transducer &#40;Philips Electronics&#44; The Netherlands&#41; by an experienced echocardiographer who was blinded to the patients included in the study&#46; Left ventricular ejection fraction &#40;LVEF&#41; and left ventricular mass index &#40;LVMI&#41; were calculated as recommended by the current guidelines&#46;<a class="elsevierStyleCrossRef" href="#bib0330"><span class="elsevierStyleSup">24</span></a> An electrocardiogram was obtained for all patients&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Blood pressure measurement</span><p id="par0050" class="elsevierStylePara elsevierViewall">Twenty-four-hour ABPM readings &#40;Oscar 2 oscillometric monitor&#44; SunTech Medical Inc&#46;&#44; Morrisville&#44; NC&#41; were assessed for all patients&#46; Appropriate cuff sizes were selected by trained nurses&#46; Measurements were taken at 15-min intervals during the day and at 30-min intervals at night&#46; Patients with fewer than 80&#37; valid measurements were excluded&#46; Patients with mean 24-hour systolic BP &#40;SBP&#41; &#8805;130 mmHg and&#47;or diastolic BP &#40;DBP&#41; &#8805;80 mmHg or mean daytime SBP &#8805;135 mmHg and&#47;or DBP &#8805;85 mmHg were diagnosed as hypertensive&#46;<a class="elsevierStyleCrossRef" href="#bib0305"><span class="elsevierStyleSup">19</span></a> A non-dipper pattern was defined as a decrease of &#60;10&#37; in SBP between daytime &#40;7&#58;00 am to 11&#58;00 pm&#41; and nighttime &#40;11&#58;00 pm to 7&#58;00 am&#41;&#46; Mean 24-hour&#44; daytime&#44; and nighttime SBP and DBP were calculated for each patient using the hourly averages of ambulatory BP recordings&#46; BP load and BP variability were recorded as additional data&#46; BP load was defined as the percentage of values reaching or exceeding 135 mmHg SBP or 85 mmHg DBP daytime and 120 mmHg SBP or 70 mmHg DBP nighttime on 24-hour BP readings&#46; 24-hour BP load was also calculated based on these cut-off values&#46; For a more reliable evaluation of BP variability&#44; we also performed an additional analysis using the weighted mean of daytime and nighttime standard deviation for both SBP and DBP&#44; as previously described&#46;<a class="elsevierStyleCrossRef" href="#bib0335"><span class="elsevierStyleSup">25</span></a></p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Statistical analysis</span><p id="par0055" class="elsevierStylePara elsevierViewall">Statistical analyses were performed using SPSS software &#40;version 21&#46;0&#59; SPSS&#44; Chicago&#44; IL&#41;&#46; Continuous data were presented as medians with interquartile range or mean &#177; SD for non-normally and normally distributed variables&#44; respectively&#46; The Shapiro-Wilk test was used to test the distribution pattern and logarithmic conversion was performed for non-normally distributed variables&#46; The study population was categorized into quartiles based on NLR levels&#46; Comparisons between groups were carried out by Kruskal-Wallis tests or analysis of variance&#44; as appropriate&#46; Differences between groups were revealed using Dunn&#39;s procedure for data without normal distribution and Bonferroni&#39;s multiple comparison post hoc test for data with normal distribution&#46; Categorical variables were summarized as percentages and compared with the chi-square test&#46; Correlations between variables were investigated by the Pearson correlation coefficient&#46; Age&#44; gender&#44; diabetes&#44; hyperlipidemia&#44; smoking status&#44; BMI&#44; serum creatinine&#44; hemoglobin&#44; fasting glucose&#44; white blood cell count&#44; platelet count&#44; log NLR&#44; total cholesterol&#44; low-density lipoprotein&#44; high-density lipoprotein cholesterol&#44; triglycerides&#44; aspirin medication&#44; LVEF and LVMI were tested by univariate linear regression analysis&#46; Multivariate regression analysis including all univariate correlates &#40;p&#60;0&#46;1&#41; was used to identify predictors for 24-hour systolic and diastolic BP and BP load&#46; For all tests&#44; statistical significance was accepted as a p value &#60;0&#46;05&#46;</p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Results</span><p id="par0060" class="elsevierStylePara elsevierViewall">Three hundred hypertensive patients &#40;47&#37; male&#41; were evaluated&#46; The mean age of the population was 48&#46;5&#177;14 years&#46; Patients were divided into quartiles according to NLR values &#40;first&#58; &#60;1&#46;55&#59; second&#58; 1&#46;55-1&#46;92&#59; third&#58; 1&#46;92-2&#46;48&#59; and fourth&#58; &#62;2&#46;48&#41;&#46; There were no differences between quartiles in terms of basal demographics&#44; cardiovascular risk factors or echocardiographic parameters &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46; Baseline laboratory findings are presented in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#46; Fasting blood glucose&#44; serum creatinine&#44; hemoglobin&#44; platelet count&#44; and lipid profile were not different across NLR quartiles&#46; White blood cell and neutrophil counts were significantly higher in upper quartiles of NLR&#46; There was also a statistically significant trend towards lower lymphocyte count in patients in the fourth quartile&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0065" class="elsevierStylePara elsevierViewall">Patients&#8217; ABPM data are shown in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#46; In the interquartile evaluation&#44; daytime SBP&#44; 24-hour DBP&#44; daytime DBP&#44; daytime SBP load&#44; 24-hour DBP load and daytime DBP load were found to be significantly higher in the upper two quartiles &#40;p&#60;0&#46;05 for all&#41;&#46; The difference was more noticeable in DBP data&#46; Dipping status and BP variability data were not significantly different between quartiles &#40;p&#62;0&#46;05&#41;&#46;</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0070" class="elsevierStylePara elsevierViewall">Subsequently&#44; the relationship between mean BP and BP load values and NLR was evaluated&#46; A positive correlation between log NLR and daytime&#44; nighttime and 24-hour BP and BP load values was identified &#40;p&#60;0&#46;05 for all&#41;&#46; Correlations of 24-hour systolic BP &#40;r&#61;0&#46;194&#59; 95&#37; confidence interval &#91;CI&#93;&#58; 0&#46;074-0&#46;320&#44; p&#61;0&#46;001&#41; and 24-hour diastolic BP &#40;r&#61;0&#46;197&#59; 95&#37; CI&#58; 0&#46;076-0&#46;307&#44; p&#61;0&#46;001&#41;&#44; 24-hour systolic BP load &#40;r&#61;0&#46;157&#59; 95&#37; CI&#58; 0&#46;032-0&#46;278&#44; p&#61;0&#46;006&#41; and 24-hour diastolic BP load &#40;r&#61;0&#46;181&#59; 95&#37; CI&#58; 0&#46;054-0&#46;295&#44; p&#61;0&#46;002&#41; with log NLR are shown in <a class="elsevierStyleCrossRef" href="#fig0005">Figure 1</a>&#46; Additionally&#44; daytime SBP load &#40;r&#61;0&#46;150&#44; 95&#37; CI&#58; 0&#46;025-0&#46;265&#44; p&#61;0&#46;009&#41;&#44; nighttime SBP load &#40;r&#61;0&#46;129&#44; 95&#37; CI&#58; 0&#46;011-0&#46;247&#44; p&#61;0&#46;026&#41;&#44; daytime DBP load &#40;r&#61;0&#46;160&#44; 95&#37; CI&#58; 0&#46;040-0&#46;273&#44; p&#61;0&#46;005&#41; and nighttime DBP load &#40;r&#61;0&#46;173&#44; 95&#37; CI&#58; 0&#46;049-0&#46;289&#44; p&#61;0&#46;003&#41; were positively correlated with log NLR&#46; Similarly&#44; a significant positive correlation was observed between mean daytime SBP &#40;r&#61;0&#46;173&#44; 95&#37; CI&#58; 0&#46;055-0&#46;292&#44; p&#61;0&#46;003&#41;&#44; nighttime SBP &#40;r&#61;0&#46;206&#44; 95&#37; CI&#58; 0&#46;091-0&#46;332&#44; p&#60; 0&#46;001&#41;&#44; daytime DBP &#40;r&#61;0&#46;170&#44; 95&#37; CI&#58; 0&#46;059-0&#46;282&#44; p&#61;0&#46;003&#41; and nighttime DBP &#40;r&#61;0&#46;214&#44; 95&#37; CI&#58; 0&#46;096-0&#46;331&#44; p&#60;0&#46;001&#41; and log NLR values&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall">After construction of multiple linear regression models with the four ABPM components associated with log NLR levels as independent variables&#44; log NLR values maintained an independent association with 24-hour SBP&#44; 24-hour DBP&#44; 24-hour SBP load &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41; and 24-hour DBP load &#40;<a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>&#41;&#46; When 24-hour SBP was taken as a continuous variable&#44; multivariate linear regression analysis revealed that 24-hour SBP was correlated with fasting blood glucose &#40;&#946;&#61;0&#46;160&#44; 95&#37; CI&#58; 0&#46;016-0&#46;088&#44; p&#61;0&#46;005&#41;&#44; female gender &#40;&#946;&#61;-0&#46;114&#44; 95&#37; CI&#58; -5&#46;409-0&#46;078&#44; p&#61;0&#46;044&#41;&#44; LVMI &#40;&#946;&#61;0&#46;194&#44; 95&#37; CI&#58; 0&#46;049-0&#46;191&#44; p&#61;0&#46;001&#41; and log NLR &#40;&#946;&#61;0&#46;208 95&#37; CI&#58; 7&#46;881-23&#46;975&#44; p&#60;0&#46;001&#41;&#46; Similarly&#44; multivariate linear regression analysis demonstrated significant associations between age &#40;&#946;&#61;-0&#46;197&#44; 95&#37; CI&#58; -0&#46;197-0&#46;047&#44; p&#61;0&#46;002&#41;&#44; LVEF &#40;&#946;&#61;-0&#46;162&#44; 95&#37; CI&#58; -0&#46;837-0&#46;149&#44; p&#61;0&#46;005&#41;&#44; log NLR &#40;&#946;&#61;0&#46;216&#44; 95&#37; CI&#58; 6&#46;119-18&#46;741&#44; p&#60;0&#46;001&#41; and 24-hour DBP&#46;</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><elsevierMultimedia ident="tbl0025"></elsevierMultimedia></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Discussion</span><p id="par0080" class="elsevierStylePara elsevierViewall">The results of our study show that in patients with untreated HTN&#44; admission NLR values and ambulatory BP and BP load measurements were correlated&#46; To our knowledge&#44; this is the first study in the literature demonstrating such a correlation between NLR and BP severity&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">Elevated NLR values are a predictor of high cardiovascular risk<a class="elsevierStyleCrossRef" href="#bib0340"><span class="elsevierStyleSup">26</span></a> and are correlated with inflammatory activity and the severity of numerous diseases&#46;<a class="elsevierStyleCrossRefs" href="#bib0345"><span class="elsevierStyleSup">27&#44;28</span></a> Increased renin-angiotensin-aldosterone system activity and CRP-mediated inflammation are involved in the inflammatory response observed in hypertensive patients&#44; and activation of peroxisome proliferator-activated receptors may protect against these effects&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">4</span></a> Angiotensin II triggers a series of inflammatory processes resulting in vascular remodeling and injury via endothelin-1 and NAD&#40;P&#41;H oxidase&#46;<a class="elsevierStyleCrossRef" href="#bib0355"><span class="elsevierStyleSup">29</span></a> Other than the vascular remodeling resulting from chronic HTN&#44; there is no other evidence indicating whether low-grade inflammation level is reflected in short-term BP values&#46; However&#44; structural vascular alterations occurring during chronic HTN&#44; along with some functional mechanisms&#44; may cause acute BP alterations and inflammation&#46;<a class="elsevierStyleCrossRef" href="#bib0360"><span class="elsevierStyleSup">30</span></a> In previous studies it was shown that high-sensitivity CRP and leukocyte count were elevated in patients experiencing acute BP increase in conditions such as hypertensive crisis&#46;<a class="elsevierStyleCrossRef" href="#bib0365"><span class="elsevierStyleSup">31</span></a> Shear stress due to high BP levels may lead to an increase in inflammation in the short term by increased expression of adhesion molecules&#44; endothelial dysfunction and NO-related mechanisms&#46;<a class="elsevierStyleCrossRef" href="#bib0370"><span class="elsevierStyleSup">32</span></a> It is known that ICAM-1 and interleukin-6 increase with increasing BP&#46;<a class="elsevierStyleCrossRef" href="#bib0375"><span class="elsevierStyleSup">33</span></a> In our study also&#44; patients with higher NLR were found to have higher ambulatory BP measurements&#44; particularly for DBP&#46; Like mean BP values&#44; the relationship of BP load with higher NLR values suggests that the inflammation observed in these patients is associated with short-term barotrauma&#46; A higher BP load means that target organs are exposed to higher pressure for a longer duration&#44; even if mean BP is normal&#46; Additionally&#44; patients with increased BP load are subject to overloading of the cardiovascular system&#44; with consequent negative impact on related structures&#46; Higher BP load may promote an inflammatory response to HTN&#46; Recent studies reporting an association between BP load and target organ damage have shown that this relationship is not independent of 24-hour BP levels&#46;<a class="elsevierStyleCrossRef" href="#bib0380"><span class="elsevierStyleSup">34</span></a> On the contrary&#44; Wang et al&#46; have shown that BP load is an independent predictor of target organ damage in patients with chronic renal disease&#46;<a class="elsevierStyleCrossRef" href="#bib0325"><span class="elsevierStyleSup">23</span></a> Higher BP load &#40;&#8216;baric impact&#8217;&#41; may cause endothelial dysfunction associated with vasopressor effects and thus may increase inflammation&#46;<a class="elsevierStyleCrossRef" href="#bib0385"><span class="elsevierStyleSup">35</span></a></p><p id="par0090" class="elsevierStylePara elsevierViewall">As a probable predictor of BP severity&#44; NLR has been the subject of antihypertensive therapy studies&#46; Antihypertensive drugs may lead to a decrease in NLR&#44; by both BP-lowering and anti-inflammatory effects&#46;<a class="elsevierStyleCrossRefs" href="#bib0390"><span class="elsevierStyleSup">36&#44;37</span></a> In previous studies non-dipping status and increased BP variability were associated with higher NLR&#46;<a class="elsevierStyleCrossRefs" href="#bib0400"><span class="elsevierStyleSup">38&#44;39</span></a> In our study&#44; the lack of difference in BP variability and non-dipper status between groups made the relationship between NLR and BP&#47;BP load clearer&#46; Furthermore&#44; increased pulse pressure is considered a significant marker of chronic inflammation and arterial stiffness&#46;<a class="elsevierStyleCrossRef" href="#bib0410"><span class="elsevierStyleSup">40</span></a> In a smaller cohort including normotensives NLR was reportedly correlated with 24-hour SBP and night-time SBP&#46;<a class="elsevierStyleCrossRef" href="#bib0415"><span class="elsevierStyleSup">41</span></a> In the same study&#44; pulse pressure was also correlated positively with NLR&#46; In our study&#44; mean pulse pressure did not differ between quartiles and therefore did not contribute significantly to the results&#46; Interestingly&#44; Gang and Yanyan showed that NLR was increased in patients suffering from HTN with hyperhomocysteinemia and was positively correlated with homocysteine levels but not with BP&#46;<a class="elsevierStyleCrossRef" href="#bib0420"><span class="elsevierStyleSup">42</span></a> In their study&#44; they also found no difference in NLR values between hypertensive and normotensive groups&#46; A single office BP measurement and lack of data on antihypertensive medication could be responsible for their results&#46;</p><p id="par0095" class="elsevierStylePara elsevierViewall">In the present study&#44; we found a weak correlation between ABPM data and log NLR values&#46; There are several possible reasons for this&#58; 24-hour ABPM provides short-term data and has limited reproducibility&#44; which makes it difficult to clarify the severity of HTN&#46; In addition&#44; the selection of a relatively low-risk cohort of hypertensive patients may have meant they had only a low-grade inflammatory response&#44; which might have weakened the correlation between NLR and severity of HTN&#46; Nevertheless&#44; despite other confounding factors such as the unknown chronicity of HTN and underlying subclinical end-organ damage&#44; the available data suggest that higher NLR is associated with higher BP and BP load&#46; Thus&#44; our study may function as a hypothesis-generating study and lead to further research&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">Our study has some limitations&#46; Firstly&#44; its cross-sectional design precludes drawing conclusions about causal relationships between NLR values and short-term ABPM results&#46; Since ABPM was performed only once in each patient&#44; the reproducibility of ambulatory BP measurements is another limitation&#46; We think that the use of BP load as an outcome is also a limitation because its importance in cardiovascular risk stratification is debatable&#46; In addition&#44; it would have been better to have evaluated leukocyte activation markers&#44; pro-inflammatory cytokines and oxidative stress markers&#46; Exclusion of patients with severe complications of HTN from the present study prevents us from generalizing our results to the whole hypertensive patient population&#46;</p></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Conclusions</span><p id="par0105" class="elsevierStylePara elsevierViewall">We showed for the first time a significant correlation between high BP load and NLR&#46; Further large-scale studies are needed to assess whether NLR can be used to predict HTN severity and to guide therapy in patients with HTN&#46;</p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Ethical disclosures</span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Protection of human and animal subjects</span><p id="par0110" class="elsevierStylePara elsevierViewall">The authors declare that no experiments were performed on humans or animals for this study&#46;</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Confidentiality of data</span><p id="par0115" class="elsevierStylePara elsevierViewall">The authors declare that they have followed the protocols of their work center on the publication of patient data&#46;</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Right to privacy and informed consent</span><p id="par0120" class="elsevierStylePara elsevierViewall">The authors declare that no patient data appear in this article&#46;</p></span></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Conflicts of interest</span><p id="par0125" class="elsevierStylePara elsevierViewall">The authors have no conflicts of interest to declare&#46;</p></span></span>"
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            0 => "Ambulatory blood pressure"
            1 => "Neutrophil-to-lymphocyte ratio"
            2 => "Hypertension"
            3 => "Inflammation"
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            0 => "Press&#227;o arterial em ambulat&#243;rio"
            1 => "Propor&#231;&#227;o neutr&#243;filos&#47;linf&#243;citos"
            2 => "Hipertens&#227;o"
            3 => "Inflama&#231;&#227;o"
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        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction and Objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">The neutrophil-to-lymphocyte ratio &#40;NLR&#41; is established as a reliable marker of systemic inflammation&#46; Low-grade inflammation has a key role in the pathogenesis and progression of hypertension &#40;HTN&#41;&#46; Blood pressure &#40;BP&#41; load&#44; defined as the percentage of abnormally elevated BP readings&#44; is a good marker of HTN severity&#46; We aimed to evaluate the relationship between HTN severity and NLR using averaged ambulatory BP readings and BP load&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">A total of 300 patients with untreated essential HTN were included in this cross-sectional study&#46; Patients were divided into quartiles according to NLR values &#40;first&#58; &#60;1&#46;55&#59; second&#58; 1&#46;55-1&#46;92&#59; third&#58; 1&#46;92-2&#46;48&#59; and fourth&#58; &#62;2&#46;48&#41;&#46; Averaged ambulatory BP values and BP load were assessed for each quartile&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">In the interquartile evaluation there were no differences between quartiles in terms of baseline demographic&#44; clinical and echocardiographic characteristics &#40;p&#62;0&#46;05&#41;&#46; Daytime systolic BP &#40;SBP&#41;&#44; 24-hour diastolic BP &#40;DBP&#41;&#44; daytime DBP&#44; daytime SBP load&#44; 24-hour DBP load and daytime DBP load were found to be significantly higher in the upper two quartiles &#40;p&#60;0&#46;05 for all&#41;&#46; In correlation analysis&#44; log NLR values were found to be positively correlated with 24-hour SBP&#44; DBP&#44; SBP load and DBP load &#40;Pearson coefficients of 0&#46;194&#44; 0&#46;197&#44; 0&#46;157 and 0&#46;181&#44; respectively&#59; p&#60;0&#46;01 for all&#41;&#46; In multivariate analysis&#44; log NLR had an independent association with 24-hour SBP and DBP and 24-hour SBP and DBP load&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">This study showed for the first time that increased NLR is independently associated with HTN severity in untreated essential HTN patients&#46;</p></span>"
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            "titulo" => "Introduction and Objective"
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            "titulo" => "Methods"
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        "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 rela&#231;&#227;o neutr&#243;filos&#47;linf&#243;citos &#40;RNL&#41; foi estabelecida como um marcador inflamat&#243;rio sist&#233;mico fi&#225;vel&#46; Uma inflama&#231;&#227;o de baixo grau tem um papel fundamental na patog&#233;nese e na progress&#227;o da hipertens&#227;o &#40;HT&#41;&#46; A carga da press&#227;o arterial &#40;PA&#41; definida como a percentagem de leituras da PA anormalmente elevadas &#233; um bom marcador da gravidade da PA&#46; O objetivo deste estudo &#233; avaliar a rela&#231;&#227;o entre a gravidade da PA e a RNL pela utiliza&#231;&#227;o da m&#233;dia de leituras ambulat&#243;rias da PA e da carga da PA&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">M&#233;todos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Um total de 300 doentes&#44; com HT essencial n&#227;o tratada&#44; foram inclu&#237;dos neste estudo transversal&#46; Os doentes foram divididos em quartis&#44; de acordo com os valores da RNL &#40;primeiro &#60;1&#44;55&#59; segundo 1&#44;55-1&#44;92&#59; terceiro 1&#44;92-2&#44;48 e o quarto &#62; 2&#44;48&#41;&#46; Os valores m&#233;dios da PA em ambulat&#243;rio e a carga da PA foram avaliados para cada quartil&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Na avalia&#231;&#227;o interquartis&#44; n&#227;o houve diferen&#231;a entre quartis nas caracter&#237;sticas demogr&#225;ficas&#44; cl&#237;nicas e ecocardiogr&#225;ficas basais &#40;p &#62; 0&#44;05&#41;&#46; A PA sist&#243;lica diurna &#40;PAS&#41;&#44; a PA diast&#243;lica &#40;PAD&#41; a 24 horas&#44; a PAD diurna&#44; a carga da PAS diurna&#44; a PAD a 24 horas e a PAD diurna foram significativamente mais elevadas nos dois quartis superiores &#40;p &#60; 0&#44;05 para todos&#41;&#46; Na an&#225;lise de correla&#231;&#227;o&#44; os valores do logaritmo de RNL foram positivamente correlacionados com a PAS a 24 horas&#44; com a PAD&#44; com a PAS carga e com a PAD carga &#40;coeficientes de Pearson de 0&#44;194&#44; 0&#44;197&#44; 0&#44;157 e 0&#44;181&#44; respetivamente&#59; p&#60;0&#44;01 para todos&#41;&#46; Na an&#225;lise multivariada&#44; os valores do logaritmo da RNL mostraram uma associa&#231;&#227;o independente com a PAS-PAD a 24 horas e com a carga da PAS-PAD a 24 horas&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclus&#227;o</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Este estudo mostrou pela primeira vez que o aumento da RNL est&#225; independentemente associado &#224; gravidade da PA nos doentes com HT essencial n&#227;o tratada&#46;</p></span>"
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          0 => array:2 [
            "identificador" => "abst0025"
            "titulo" => "Introdu&#231;&#227;o e objetivos"
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          1 => array:2 [
            "identificador" => "abst0030"
            "titulo" => "M&#233;todos"
          ]
          2 => array:2 [
            "identificador" => "abst0035"
            "titulo" => "Resultados"
          ]
          3 => array:2 [
            "identificador" => "abst0040"
            "titulo" => "Conclus&#227;o"
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      0 => array:7 [
        "identificador" => "fig0005"
        "etiqueta" => "Figure 1"
        "tipo" => "MULTIMEDIAFIGURA"
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        "mostrarDisplay" => false
        "figura" => array:1 [
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          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Pearson&#39;s correlation analysis demonstrating correlations between NLR and &#40;A&#41; 24-hour systolic BP&#59; &#40;B&#41; 24-hour systolic BP load&#59; &#40;C&#41; 24-hour diastolic BP&#59; and &#40;D&#41; 24-hour diastolic BP load&#46; BP&#58; blood pressure&#59; NLR&#58; neutrophil-to-lymphocyte ratio&#46;</p>"
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      1 => array:8 [
        "identificador" => "tbl0005"
        "etiqueta" => "Table 1"
        "tipo" => "MULTIMEDIATABLA"
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          "leyenda" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">BMI&#58; body mass index&#59; IVS&#58; interventricular septum&#59; LVEDD&#58; left ventricular end-diastolic diameter&#59; LVEF&#58; left ventricular ejection fraction&#59; LVMI&#58; left ventricular mass index&#59; NLR&#58; neutrophil-to-lymphocyte ratio&#46; Data are expressed as mean &#177; standard deviation&#44; median with interquartile range&#44; or percentage frequency&#44; as appropriate&#46; NLR quartiles&#58; first&#58; 0&#46;74-1&#46;55&#59; second&#58; 1&#46;55-1&#46;92&#59; third&#58; 1&#46;92-2&#46;48&#59; fourth&#58; 2&#46;48-6&#46;64&#46;</p>"
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                  <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">All &#40;n&#61;300&#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">1st quartile &#40;n&#61;75&#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">2nd quartile &#40;n&#61;75&#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">3rd quartile &#40;n&#61;75&#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">4th quartile &#40;n&#61;75&#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">p<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&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"><span class="elsevierStyleItalic">Age&#44; years</span>&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;5&#177;14&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;7&#177;14&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;5&#177;13&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;7&#177;15&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&#177;14&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;776&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="elsevierStyleItalic">Male&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">141 &#40;47&#41;&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;49&#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;53&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">32 &#40;43&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">32 &#40;43&#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;457&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="elsevierStyleItalic">BMI&#44; kg&#47;m</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">2</span></span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">22&#46;4 &#40;21&#46;1-23&#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">22&#46;8 &#40;21&#46;3-23&#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">22&#46;1 &#40;20&#46;9-23&#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">22&#46;3 &#40;21&#46;1-23&#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">22&#46;1 &#40;21&#46;1-23&#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">0&#46;543&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="elsevierStyleItalic">Diabetes&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">41 &#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">7 &#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">12 &#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;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">13 &#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">0&#46;479&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="elsevierStyleItalic">Hyperlipidemia&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">21 &#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">1 &#40;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">8 &#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">8 &#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">4 &#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;071&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="elsevierStyleItalic">Smoking&#44; n &#40;&#37;&#41;</span>&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;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">8 &#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">12 &#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">11 &#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">5 &#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">0&#46;290&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="elsevierStyleItalic">Aspirin therapy&#44; n &#40;&#37;&#41;</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 &#40;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">1 &#40;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">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1 &#40;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">2 &#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">0&#46;568&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="7" 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="7" align="left" valign="top"><span class="elsevierStyleItalic">Echocardiographic characteristics</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>IVS&#44; mm&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;4&#177;1&#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">10&#46;2&#177;1&#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">10&#46;5&#177;1&#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">10&#46;2&#177;1&#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">10&#46;5&#177;1&#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">0&#46;578&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>Posterior wall&#44; mm&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">9&#46;9&#177;1&#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">9&#46;7&#177;1&#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">10&#46;0&#177;1&#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">9&#46;8&#177;1&#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">9&#46;9&#177;1&#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">0&#46;666&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>LVEDD&#44; mm&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">46&#46;1&#177;3&#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">46&#46;4&#177;3&#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">45&#46;8&#177;2&#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">46&#46;2&#177;3&#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">46&#46;2&#177;3&#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">0&#46;822&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&#44; &#37;&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;9&#177;2&#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">61&#46;7&#177;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">62&#46;1&#177;2&#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">61&#46;6&#177;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">62&#46;3&#177; 3&#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">0&#46;494&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>LVMI&#44; g&#47;m<span class="elsevierStyleSup">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">93&#46;3&#177;19&#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">92&#46;6&#177;19&#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">94&#46;0&#177;19&#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">92&#46;3&#177;18&#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">94&#46;3&#177;20&#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">0&#46;897&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
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                0 => "xTab1351722.png"
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            0 => array:3 [
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              "etiqueta" => "a"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Comparison between groups&#46;</p>"
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        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Baseline characteristics of patients by neutrophil-to-lymphocyte ratio quartiles&#46;</p>"
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      ]
      2 => array:8 [
        "identificador" => "tbl0010"
        "etiqueta" => "Table 2"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
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        "detalles" => array:1 [
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          "leyenda" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">HDL&#58; high-density lipoprotein&#59; LDL&#58; low-density lipoprotein&#59; NLR&#58; neutrophil-to-lymphocyte ratio&#59; WBC&#58; white blood cell count&#46; Data are expressed as mean &#177; standard deviation or median with interquartile range&#44; as appropriate&#46; NLR quartiles&#58; first&#58; 0&#46;74-1&#46;55&#59; second&#58; 1&#46;55-1&#46;92&#59; third&#58; 1&#46;92-2&#46;48&#59; fourth&#58; 2&#46;48-6&#46;64&#46;</p>"
          "tablatextoimagen" => array:1 [
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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" 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">All &#40;n&#61;300&#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">1st quartile &#40;n&#61;75&#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">2nd quartile &#40;n&#61;75&#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">3rd quartile &#40;n&#61;75&#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">4th quartile &#40;n&#61;75&#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">p<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">a</span></a>&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">Fasting blood glucose&#44; mg&#47;dl&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">90 &#40;81-102&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">89 &#40;81-99&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">90 &#40;82-104&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">90 &#40;82-99&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">91 &#40;81-106&#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;914&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">Serum creatinine&#44; mg&#47;dl&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;85 &#40;0&#46;72-1&#46;0&#41;&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;83 &#40;0&#46;70-1&#46;0&#41;&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;86 &#40;0&#46;74-0&#46;97&#41;&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;81 &#40;0&#46;70-0&#46;98&#41;&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;88 &#40;0&#46;73-1&#46;03&#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;679&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">Hemoglobin&#44; g&#47;dl&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">14&#46;3&#177;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">14&#46;4&#177;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">14&#46;4&#177;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">14&#46;4&#177;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">14&#46;1&#177;1&#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">0&#46;374&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">WBC&#44; 10<span class="elsevierStyleSup">3</span>&#47;mm<span class="elsevierStyleSup">3</span>&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;8&#177;1&#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">6&#46;8&#177;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">7&#46;8&#177;1&#46;4<a class="elsevierStyleCrossRef" href="#tblfn0020"><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="left" valign="top">7&#46;9&#177;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">8&#46;6&#177;2&#46;0<a class="elsevierStyleCrossRef" href="#tblfn0015"><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">&#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">Neutrophils&#44; 10<span class="elsevierStyleSup">3</span>&#47;mm<span class="elsevierStyleSup">3</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">4&#46;7&#177;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">3&#46;4&#177;0&#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">4&#46;3&#177;0&#46;7<a class="elsevierStyleCrossRef" href="#tblfn0025"><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="left" valign="top">4&#46;9&#177;1&#46;0<a class="elsevierStyleCrossRef" href="#tblfn0015"><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="left" valign="top">5&#46;9&#177;1&#46;5<a class="elsevierStyleCrossRef" href="#tblfn0025"><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">&#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">Lymphocytes&#44; 10<span class="elsevierStyleSup">3</span>&#47;mm<span class="elsevierStyleSup">3</span>&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;3&#177;0&#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;7&#177;0&#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;5&#177;0&#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;2&#177;0&#46;4<a class="elsevierStyleCrossRef" href="#tblfn0020"><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="left" valign="top">1&#46;9&#177;0&#46;4<a class="elsevierStyleCrossRef" href="#tblfn0025"><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">&#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">NLR&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;09&#177;0&#46;83&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&#177;0&#46;18&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;71&#177;0&#46;10&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;19&#177;0&#46;16&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;2&#177;0&#46;80&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></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Platelets&#44; 10<span class="elsevierStyleSup">3</span>&#47;mm<span class="elsevierStyleSup">3</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">265&#177;67&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">251&#177;64&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">263&#177;62&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">269&#177;64&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">279&#177;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;075&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">Total cholesterol&#44; mg&#47;dl&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">202&#177;40&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">205&#177;34&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">206&#177;38&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">201&#177;45&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">198&#177;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;582&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">HDL cholesterol&#44; mg&#47;dl&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">46 &#40;40-54&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">45 &#40;40-56&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">47 &#40;40-55&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">46 &#40;39-55&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">45 &#40;40-51&#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;540&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">LDL cholesterol&#44; mg&#47;dl&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">143&#177;35&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">144&#177;32&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">148&#177;35&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">142&#177;37&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">140&#177;35&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;611&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">Triglycerides&#44; mg&#47;dl&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">143 &#40;94-215&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">145 &#40;90-214&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">159 &#40;102-217&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">135 &#40;91-224&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">126 &#40;91-183&#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;247&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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              "identificador" => "tblfn0015"
              "etiqueta" => "b"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0015">p&#60;0&#46;05 compared with the previous quartile&#46;</p>"
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            2 => array:3 [
              "identificador" => "tblfn0020"
              "etiqueta" => "c"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0020">p&#60;0&#46;01 compared with the previous quartile&#46;</p>"
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            3 => array:3 [
              "identificador" => "tblfn0025"
              "etiqueta" => "d"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0025">p&#60;0&#46;001 compared with the previous quartile&#46;</p>"
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        "descripcion" => array:1 [
          "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Laboratory parameters of patients by neutrophil-to-lymphocyte ratio quartiles&#46;</p>"
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        "identificador" => "tbl0015"
        "etiqueta" => "Table 3"
        "tipo" => "MULTIMEDIATABLA"
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        "detalles" => array:1 [
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            "identificador" => "at3"
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        "tabla" => array:3 [
          "leyenda" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">DBP&#58; diastolic blood pressure&#59; NLR&#58; neutrophil-to-lymphocyte ratio&#59; SBP&#58; systolic blood pressure&#59; SD&#58; standard deviation&#59; wSD&#58; weighted standard deviation&#46; Data are expressed as mean &#177; standard deviation &#40;SD&#41;&#44; median with interquartile range&#44; or percentage frequency&#44; as appropriate&#46; Bold values indicate statistical significance&#46; NLR quartiles&#58; first&#58; 0&#46;74-1&#46;55&#59; second&#58; 1&#46;55-1&#46;92&#59; third&#58; 1&#46;92-2&#46;48&#59; fourth&#58; 2&#46;48-6&#46;64&#46;</p>"
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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" 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">All &#40;n&#61;300&#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">1st quartile &#40;n&#61;75&#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">2nd quartile &#40;n&#61;75&#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">3rd quartile &#40;n&#61;75&#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">4th quartile &#40;n&#61;75&#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">p<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">a</span></a>&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">24-h SBP&#44; mmHg&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">139&#46;7&#177;12&#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">137&#46;0&#177;11&#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">139&#46;0&#177;10&#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">140&#46;4&#177;11&#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">142&#46;2&#177;14&#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;09&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">Daytime SBP&#44; mmHg&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">142&#46;4&#177;11&#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">139&#46;7&#177;10&#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">141&#46;5&#177;11&#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">143&#46;5&#177;11&#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">144&#46;7&#177;13&#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"><span class="elsevierStyleBold">0&#46;048</span>&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">Nighttime SBP&#44; mmHg&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">127 &#40;118-137&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">126 &#40;117-135&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">125 &#40;118-133&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">127 &#40;118-139&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">132 &#40;117-140&#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;295&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">24-h DBP&#44; mmHg&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">83&#46;6&#177;9&#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">80&#46;7&#177;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">83&#46;0&#177;8&#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">84&#46;6&#177;8&#46;6<a class="elsevierStyleCrossRef" href="#tblfn0035"><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">85&#46;8&#177;9&#46;5<a class="elsevierStyleCrossRef" href="#tblfn0040"><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"><span class="elsevierStyleBold">0&#46;003</span>&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">Daytime DBP&#44; mmHg&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">85&#46;7&#177;9&#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">82&#46;8&#177;8&#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">84&#46;9&#177;8&#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">87&#46;1&#177;8&#46;7<a class="elsevierStyleCrossRef" href="#tblfn0040"><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">87&#46;9&#177;9&#46;5<a class="elsevierStyleCrossRef" href="#tblfn0040"><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"><span class="elsevierStyleBold">0&#46;001</span>&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">Nighttime DBP&#44; mmHg&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;68-82&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">71 &#40;63-80&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">73 &#40;68-80&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">74 &#40;68-82&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">77 &#40;70-85&#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;059&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">Non-dippers&#44; n &#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">151 &#40;51&#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;54&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">30 &#40;40&#41;&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;49&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">44 &#40;59&#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;126&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">SD of 24-h SBP&#44; mmHg&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;13&#46;2-18&#46;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">15&#46;2 &#40;12&#46;6-18&#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">16&#46;1 &#40;14&#46;4-18&#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">15&#46;1 &#40;12&#46;4-18&#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">15&#46;8 &#40;13&#46;0-18&#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;170&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">SD of 24-h DBP&#44; mmHg&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;4 &#40;9&#46;5-13&#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">11&#46;2 &#40;9&#46;2-13&#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">11&#46;9 &#40;10&#46;6-14&#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">11&#46;1 &#40;9&#46;3-13&#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">11&#46;1 &#40;9&#46;1-14&#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">0&#46;374&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">wSD of SBP&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;9 &#40;11&#46;7-16&#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">13&#46;4 &#40;11&#46;5-15&#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">14&#46;8 &#40;13&#46;0-16&#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">13&#46;2 &#40;11&#46;6-17&#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">14&#46;1 &#40;11&#46;5-15&#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;152&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">wSD of DBP&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;2 &#40;8&#46;6-12&#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">9&#46;9 &#40;8&#46;1-11&#46;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">10&#46;4 &#40;9&#46;1-12&#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">10&#46;1 &#40;8&#46;6-12&#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">10&#46;0 &#40;8&#46;3-12&#46;2&#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;469&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">24-h pulse pressure&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;1&#177;9&#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">56&#46;3&#177;9&#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">55&#46;8&#177;9&#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">56&#46;0&#177;8&#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">56&#46;4&#177;9&#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">0&#46;993&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">24-h SBP load&#44; &#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">60&#46;2&#177;23&#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">54&#46;8&#177;23&#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">58&#46;8&#177;21&#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">63&#46;2&#177;22&#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">63&#46;8&#177;25&#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">0&#46;084&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">Daytime SBP load&#44; &#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">59&#46;1&#177;24&#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">53&#46;3&#177;23&#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">57&#46;4&#177;22&#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">62&#46;9&#177;23&#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">62&#46;6&#177;26&#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"><span class="elsevierStyleBold">0&#46;045</span>&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">Nighttime SBP load&#44; &#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">71 &#40;43-100&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">57 &#40;32-90&#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;43-86&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">71 &#40;43-100&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">83 &#40;43-100&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;454&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">24-h DBP load&#44; &#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">50&#46;9&#177;26&#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">42&#46;2&#177;26&#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">48&#46;6&#177;23&#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">55&#46;8&#177;26&#46;5<a class="elsevierStyleCrossRef" href="#tblfn0040"><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">56&#46;8&#177;26&#46;2<a class="elsevierStyleCrossRef" href="#tblfn0040"><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"><span class="elsevierStyleBold">0&#46;001</span>&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">Daytime DBP load&#44; &#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">48&#46;4&#177;27&#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">39&#46;5&#177;26&#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">45&#46;6&#177;25&#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">54&#46;5&#177;28&#46;3<a class="elsevierStyleCrossRef" href="#tblfn0040"><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&#46;0&#177;27&#46;7<a class="elsevierStyleCrossRef" href="#tblfn0040"><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"><span class="elsevierStyleBold">0&#46;002</span>&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">Nighttime DBP load&#44; &#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">60 &#40;33-86&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">57 &#40;26-86&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">57 &#40;33-86&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">67 &#40;43-86&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">71 &#40;43-100&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;087&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
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                0 => "xTab1351719.png"
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            0 => array:3 [
              "identificador" => "tblfn0030"
              "etiqueta" => "a"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0030">Comparison between groups&#46;</p>"
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            1 => array:3 [
              "identificador" => "tblfn0035"
              "etiqueta" => "b"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0035">p&#60;0&#46;05 compared with first quartile&#46;</p>"
            ]
            2 => array:3 [
              "identificador" => "tblfn0040"
              "etiqueta" => "c"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0040">p&#60;0&#46;01 compared with first quartile&#46;</p>"
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Comparison of ambulatory blood pressure monitoring data across neutrophil-to-lymphocyte ratio quartiles&#46;</p>"
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      ]
      4 => array:8 [
        "identificador" => "tbl0020"
        "etiqueta" => "Table 4"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at4"
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        "tabla" => array:2 [
          "leyenda" => "<p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">BMI&#58; body mass index&#59; CI&#58; confidence interval&#59; LVEF&#58; left ventricular ejection fraction&#59; LVMI&#58; left ventricular mass index&#59; NLR&#58; neutrophil-to-lymphocyte ratio&#46; Bold values indicate statistical significance&#46;</p>"
          "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-with-role" title="table-head ; entry_with_role_rowhead " align="left" valign="top" scope="col">Variables&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Univariate</th><th class="td" title="table-head  " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Multivariate</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">&#946;&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">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">&#946;&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">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-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Female&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;113&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;6-0&#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">0&#46;05&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;04&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;257-4&#46;523&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;566&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">Age&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;142&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;047-0&#46;410&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top"><span class="elsevierStyleBold">0&#46;014</span>&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;063&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;088-0&#46;292&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;293&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">BMI&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;102&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;179-3&#46;431&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;077&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;097&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;188-3&#46;266&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;08&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">Fasting blood glucose&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;193&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;052-0&#46;194&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top"><span class="elsevierStyleBold">0&#46;001</span>&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;153&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;024-0&#46;170&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top"><span class="elsevierStyleBold">0&#46;009</span>&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">Hemoglobin&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;096&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;274-3&#46;357&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;096&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;121&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;199-4&#46;077&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;075&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">LVEF&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;104&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;713-0&#46;078&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;073&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;081&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;517-0&#46;238&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;153&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">LVMI&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;241&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;156-0&#46;423&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top"><span class="elsevierStyleBold">&#60;0&#46;001</span>&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;151&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;04-0&#46;325&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top"><span class="elsevierStyleBold">0&#46;012</span>&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">Log NLR&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;157&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;643-40&#46;293&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top"><span class="elsevierStyleBold">0&#46;006</span>&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;174&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">9&#46;818-42&#46;135&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top"><span class="elsevierStyleBold">0&#46;002</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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          "en" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">Univariate and multivariate linear regression models for 24-hour systolic blood pressure load&#46;</p>"
        ]
      ]
      5 => array:8 [
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        "etiqueta" => "Table 5"
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        "detalles" => array:1 [
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        "tabla" => array:2 [
          "leyenda" => "<p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">CI&#58; confidence interval&#59; HDL&#58; high-density lipoprotein&#59; NLR&#58; neutrophil-to-lymphocyte ratio&#46; Bold values indicate statistical significance&#46;</p>"
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            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-with-role" title="table-head ; entry_with_role_rowhead " align="left" valign="top" scope="col">Variables&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Univariate</th><th class="td" title="table-head  " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Multivariate</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">&#946;&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">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">&#946;&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">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-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Age&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;186&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;539-0&#46;134&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top"><span class="elsevierStyleBold">0&#46;001</span>&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;178&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;525-0&#46;118&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top"><span class="elsevierStyleBold">0&#46;002</span>&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">Creatinine&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;099&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;074-1&#46;093&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;087&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;077&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;176-0&#46;964&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;174&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">HDL cholesterol&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;099&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;545-0&#46;038&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;088&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;043&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;402-0&#46;179&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;451&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">Log NLR&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;181&nbsp;\t\t\t\t\t\t\n
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Article information

ISSN: 21742049
Original language: English

DOI:10.1016/j.repce.2017.02.003

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Year/Month	Html	Pdf	Total

2024 November	7	6	13
2024 October	54	27	81
2024 September	62	22	84
2024 August	67	27	94
2024 July	49	25	74
2024 June	40	23	63
2024 May	46	26	72
2024 April	37	31	68
2024 March	36	27	63
2024 February	27	35	62
2024 January	36	29	65
2023 December	32	28	60
2023 November	40	26	66
2023 October	24	12	36
2023 September	29	19	48
2023 August	36	20	56
2023 July	33	9	42
2023 June	32	17	49
2023 May	42	24	66
2023 April	21	2	23
2023 March	44	24	68
2023 February	28	18	46
2023 January	20	15	35
2022 December	40	18	58
2022 November	51	18	69
2022 October	41	18	59
2022 September	19	28	47
2022 August	24	17	41
2022 July	38	30	68
2022 June	17	17	34
2022 May	17	22	39
2022 April	16	19	35
2022 March	14	31	45
2022 February	27	23	50
2022 January	19	31	50
2021 December	18	25	43
2021 November	30	39	69
2021 October	30	34	64
2021 September	23	25	48
2021 August	26	28	54
2021 July	13	19	32
2021 June	21	11	32
2021 May	30	42	72
2021 April	42	30	72
2021 March	78	19	97
2021 February	42	21	63
2021 January	25	14	39
2020 December	27	7	34
2020 November	31	19	50
2020 October	21	15	36
2020 September	41	10	51
2020 August	15	5	20
2020 July	29	10	39
2020 June	33	8	41
2020 May	32	6	38
2020 April	37	12	49
2020 March	35	8	43
2020 February	50	21	71
2020 January	34	9	43
2019 December	32	8	40
2019 November	32	7	39
2019 October	24	3	27
2019 September	25	8	33
2019 August	32	9	41
2019 July	34	12	46
2019 June	20	8	28
2019 May	36	12	48
2019 April	17	10	27
2019 March	86	9	95
2019 February	83	11	94
2019 January	83	11	94
2018 December	91	7	98
2018 November	78	16	94
2018 October	189	16	205
2018 September	39	13	52
2018 August	41	15	56
2018 July	33	7	40
2018 June	54	17	71
2018 May	82	16	98
2018 April	261	10	271
2018 March	129	11	140
2018 February	84	8	92
2018 January	152	4	156
2017 December	82	9	91
2017 November	39	15	54
2017 October	24	12	36
2017 September	28	18	46
2017 August	24	8	32
2017 July	17	12	29
2017 June	48	12	60
2017 May	45	7	52
2017 April	29	11	40
2017 March	76	21	97
2017 February	7	4	11

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