que se leu este artigo
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BP: blood pressure; NLR: neutrophil-to-lymphocyte ratio.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Tolga Çimen, Hamza Sunman, Tolga Han Efe, Mehmet Erat, Haluk Furkan Şahan, Engin Algül, İlkin Guliyev, Ahmet Akyel, Mehmet Doğan, Sadık Açıkel, Ekrem Yeter" "autores" => array:11 [ 0 => array:2 [ "nombre" => "Tolga" "apellidos" => "Çimen" ] 1 => array:2 [ "nombre" => "Hamza" "apellidos" => "Sunman" ] 2 => array:2 [ "nombre" => "Tolga Han" "apellidos" => "Efe" ] 3 => array:2 [ "nombre" => "Mehmet" "apellidos" => "Erat" ] 4 => array:2 [ "nombre" => "Haluk Furkan" "apellidos" => "Şahan" ] 5 => array:2 [ "nombre" => "Engin" "apellidos" => "Algül" ] 6 => array:2 [ "nombre" => "İlkin" "apellidos" => "Guliyev" ] 7 => array:2 [ "nombre" => "Ahmet" "apellidos" => "Akyel" ] 8 => array:2 [ "nombre" => "Mehmet" "apellidos" => "Doğan" ] 9 => array:2 [ "nombre" => "Sadık" "apellidos" => "Açıkel" ] 10 => array:2 [ "nombre" => "Ekrem" "apellidos" => "Yeter" ] ] ] ] ] "idiomaDefecto" => "en" "Traduccion" => array:1 [ "en" => array:9 [ "pii" => "S0870255116303869" "doi" => "10.1016/j.repc.2016.07.009" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0870255116303869?idApp=UINPBA00004E" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2174204917300272?idApp=UINPBA00004E" "url" => "/21742049/0000003600000002/v1_201702240018/S2174204917300272/v1_201702240018/en/main.assets" ] ] "itemSiguiente" => array:20 [ "pii" => "S0870255116303894" "issn" => "08702551" "doi" => "10.1016/j.repc.2016.12.003" "estado" => "S300" "fechaPublicacion" => "2017-02-01" "aid" => "936" "copyright" => "Sociedade Portuguesa de Cardiologia" "documento" => "simple-article" "crossmark" => 1 "licencia" => "http://creativecommons.org/licenses/by-nc-nd/4.0/" "subdocumento" => "dis" "cita" => "Rev Port Cardiol. 2017;36:107-9" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:2 [ "total" => 2462 "formatos" => array:3 [ "EPUB" => 183 "HTML" => 1799 "PDF" => 480 ] ] "en" => array:10 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Editorial comment</span>" "titulo" => "Neutrophil-to-lymphocyte ratio and ambulatory blood pressure: Exploring the link between inflammation and hypertension" "tienePdf" => "en" "tieneTextoCompleto" => "en" "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "107" "paginaFinal" => "109" ] ] "titulosAlternativos" => array:1 [ "pt" => array:1 [ "titulo" => "Relação neutrófilos/linfócitos e pressão arterial ambulatória. 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BP: blood pressure; NLR: neutrophil-to-lymphocyte ratio.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Hypertension (HTN) is a common condition that results in damage to important target organs including the heart, kidney and brain.<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">1,2</span></a> Low-grade inflammation has a key role in its pathogenesis and progression.<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.<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">4</span></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"><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.<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">6</span></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"><span class="elsevierStyleSup">7,8</span></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"><span class="elsevierStyleSup">9</span></a> It has been shown to have prognostic significance in various conditions such as coronary artery disease,<a class="elsevierStyleCrossRefs" href="#bib0260"><span class="elsevierStyleSup">10,11</span></a> malignancy,<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">12</span></a> heart failure,<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">13</span></a> and cerebral and peripheral artery disease.<a class="elsevierStyleCrossRefs" href="#bib0280"><span class="elsevierStyleSup">14,15</span></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"><span class="elsevierStyleSup">16</span></a> NLR is a good predictor in high-risk conditions such as resistant HTN and non-dipper HTN.<a class="elsevierStyleCrossRefs" href="#bib0295"><span class="elsevierStyleSup">17,18</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">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"><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.<a class="elsevierStyleCrossRef" href="#bib0310"><span class="elsevierStyleSup">20</span></a> However, it may have limitations in patients with ‘high-normal’ BP.<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">21</span></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"><span class="elsevierStyleSup">22,23</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">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.</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. 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 >12.0×10<span class="elsevierStyleSup">3</span>/mm<span class="elsevierStyleSup">3</span>), history of malignancy, chronic renal disease (estimated glomerular filtration rate <60 ml/min/1.73 m<span class="elsevierStyleSup">2</span>), 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.</p><p id="par0030" class="elsevierStylePara elsevierViewall">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.</p><p id="par0035" class="elsevierStylePara elsevierViewall">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.</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 (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.</p><p id="par0045" class="elsevierStylePara elsevierViewall">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"><span class="elsevierStyleSup">24</span></a> An electrocardiogram was obtained for all patients.</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 (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"><span class="elsevierStyleSup">19</span></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"><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 (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.</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 (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.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0065" class="elsevierStylePara elsevierViewall">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).</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0070" class="elsevierStylePara elsevierViewall">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.</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, 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.</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, 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.</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.<a class="elsevierStyleCrossRefs" href="#bib0345"><span class="elsevierStyleSup">27,28</span></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"><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(P)H oxidase.<a class="elsevierStyleCrossRef" href="#bib0355"><span class="elsevierStyleSup">29</span></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"><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.<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, endothelial dysfunction and NO-related mechanisms.<a class="elsevierStyleCrossRef" href="#bib0370"><span class="elsevierStyleSup">32</span></a> It is known that ICAM-1 and interleukin-6 increase with increasing BP.<a class="elsevierStyleCrossRef" href="#bib0375"><span class="elsevierStyleSup">33</span></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"><span class="elsevierStyleSup">34</span></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"><span class="elsevierStyleSup">23</span></a> Higher BP load (‘baric impact’) may cause endothelial dysfunction associated with vasopressor effects and thus may increase inflammation.<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, 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"><span class="elsevierStyleSup">36,37</span></a> In previous studies non-dipping status and increased BP variability were associated with higher NLR.<a class="elsevierStyleCrossRefs" href="#bib0400"><span class="elsevierStyleSup">38,39</span></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"><span class="elsevierStyleSup">40</span></a> In a smaller cohort including normotensives NLR was reportedly correlated with 24-hour SBP and night-time SBP.<a class="elsevierStyleCrossRef" href="#bib0415"><span class="elsevierStyleSup">41</span></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"><span class="elsevierStyleSup">42</span></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.</p><p id="par0095" class="elsevierStylePara elsevierViewall">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.</p><p id="par0100" class="elsevierStylePara elsevierViewall">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.</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. 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.</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.</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.</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.</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.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres799842" "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" => "xpalclavsec798350" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres799841" "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" => "xpalclavsec798351" "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" => "xpalclavsec798350" "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" => "xpalclavsec798351" "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" => "<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 (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.</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. 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.</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, 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.</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.</p></span>" "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" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Introdução e objetivos</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">A 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.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Métodos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Um 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.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Na 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.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusão</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Este estudo mostrou pela primeira vez que o aumento da RNL está independentemente associado à gravidade da PA nos doentes com HT essencial não tratada.</p></span>" "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" => 2697 "Ancho" => 3353 "Tamanyo" => 698912 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">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.</p>" ] ] 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" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">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.</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" 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"><span class="elsevierStyleSup">a</span></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"><span class="elsevierStyleItalic">Age, years</span> \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"><span class="elsevierStyleItalic">Male, n (%)</span> \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"><span class="elsevierStyleItalic">BMI, kg/m</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">2</span></span> \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"><span class="elsevierStyleItalic">Diabetes, n (%)</span> \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"><span class="elsevierStyleItalic">Hyperlipidemia, n (%)</span> \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"><span class="elsevierStyleItalic">Smoking, n (%)</span> \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"><span class="elsevierStyleItalic">Aspirin therapy, n (%)</span> \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"><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, 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"><span class="elsevierStyleHsp" style=""></span>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"><span class="elsevierStyleHsp" style=""></span>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"><span class="elsevierStyleHsp" style=""></span>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"><span class="elsevierStyleHsp" style=""></span>LVMI, g/m<span class="elsevierStyleSup">2</span> \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 => "xTab1341881.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Comparison between groups.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Baseline characteristics of patients by neutrophil-to-lymphocyte ratio quartiles.</p>" ] ] 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" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">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.</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" 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"><span class="elsevierStyleSup">a</span></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, 10<span class="elsevierStyleSup">3</span>/mm<span class="elsevierStyleSup">3</span> \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"><span class="elsevierStyleSup">c</span></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"><span class="elsevierStyleSup">b</span></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, 10<span class="elsevierStyleSup">3</span>/mm<span class="elsevierStyleSup">3</span> \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"><span class="elsevierStyleSup">d</span></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"><span class="elsevierStyleSup">b</span></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"><span class="elsevierStyleSup">d</span></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, 10<span class="elsevierStyleSup">3</span>/mm<span class="elsevierStyleSup">3</span> \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"><span class="elsevierStyleSup">c</span></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"><span class="elsevierStyleSup">d</span></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, 10<span class="elsevierStyleSup">3</span>/mm<span class="elsevierStyleSup">3</span> \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 => "xTab1341880.png" ] ] ] "notaPie" => array:4 [ 0 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0010">Comparison between groups.</p>" ] 1 => array:3 [ "identificador" => "tblfn0015" "etiqueta" => "b" "nota" => "<p class="elsevierStyleNotepara" id="npar0015">p<0.05 compared with the previous quartile.</p>" ] 2 => array:3 [ "identificador" => "tblfn0020" "etiqueta" => "c" "nota" => "<p class="elsevierStyleNotepara" id="npar0020">p<0.01 compared with the previous quartile.</p>" ] 3 => array:3 [ "identificador" => "tblfn0025" "etiqueta" => "d" "nota" => "<p class="elsevierStyleNotepara" id="npar0025">p<0.001 compared with the previous quartile.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Laboratory parameters of patients by neutrophil-to-lymphocyte ratio quartiles.</p>" ] ] 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" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">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.</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" 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"><span class="elsevierStyleSup">a</span></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"><span class="elsevierStyleBold">0.048</span> \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"><span class="elsevierStyleSup">b</span></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"><span class="elsevierStyleSup">c</span></a> \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">0.003</span> \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"><span class="elsevierStyleSup">c</span></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"><span class="elsevierStyleSup">c</span></a> \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">0.001</span> \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"><span class="elsevierStyleBold">0.045</span> \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"><span class="elsevierStyleSup">c</span></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"><span class="elsevierStyleSup">c</span></a> \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">0.001</span> \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"><span class="elsevierStyleSup">c</span></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"><span class="elsevierStyleSup">c</span></a> \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">0.002</span> \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 => "xTab1341879.png" ] ] ] "notaPie" => array:3 [ 0 => array:3 [ "identificador" => "tblfn0030" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0030">Comparison between groups.</p>" ] 1 => array:3 [ "identificador" => "tblfn0035" "etiqueta" => "b" "nota" => "<p class="elsevierStyleNotepara" id="npar0035">p<0.05 compared with first quartile.</p>" ] 2 => array:3 [ "identificador" => "tblfn0040" "etiqueta" => "c" "nota" => "<p class="elsevierStyleNotepara" id="npar0040">p<0.01 compared with first quartile.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Comparison of ambulatory blood pressure monitoring data across neutrophil-to-lymphocyte ratio quartiles.</p>" ] ] 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" => "<p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">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.</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 \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"><span class="elsevierStyleBold">0.014</span> \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"><span class="elsevierStyleBold">0.001</span> \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"><span class="elsevierStyleBold">0.009</span> \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"><span class="elsevierStyleBold"><0.001</span> \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"><span class="elsevierStyleBold">0.012</span> \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"><span class="elsevierStyleBold">0.006</span> \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"><span class="elsevierStyleBold">0.002</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1341878.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">Univariate and multivariate linear regression models for 24-hour systolic blood pressure load.</p>" ] ] 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" => "<p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">CI: confidence interval; HDL: high-density lipoprotein; NLR: neutrophil-to-lymphocyte ratio. Bold values indicate statistical significance.</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 \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"><span class="elsevierStyleBold">0.001</span> \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"><span class="elsevierStyleBold">0.002</span> \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"><span class="elsevierStyleBold">0.002</span> \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"><span class="elsevierStyleBold">0.002</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1341877.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">Univariate and multivariate linear regression models for 24-hour diastolic blood pressure load.</p>" ] ] ] "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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Ano/Mês | Html | Total | |
---|---|---|---|
2024 Novembro | 6 | 3 | 9 |
2024 Outubro | 49 | 41 | 90 |
2024 Setembro | 48 | 28 | 76 |
2024 Agosto | 49 | 30 | 79 |
2024 Julho | 45 | 30 | 75 |
2024 Junho | 50 | 28 | 78 |
2024 Maio | 37 | 15 | 52 |
2024 Abril | 41 | 27 | 68 |
2024 Maro | 25 | 22 | 47 |
2024 Fevereiro | 32 | 19 | 51 |
2024 Janeiro | 24 | 30 | 54 |
2023 Dezembro | 24 | 28 | 52 |
2023 Novembro | 40 | 30 | 70 |
2023 Outubro | 17 | 16 | 33 |
2023 Setembro | 29 | 18 | 47 |
2023 Agosto | 27 | 18 | 45 |
2023 Julho | 28 | 16 | 44 |
2023 Junho | 33 | 16 | 49 |
2023 Maio | 48 | 24 | 72 |
2023 Abril | 23 | 4 | 27 |
2023 Maro | 74 | 35 | 109 |
2023 Fevereiro | 55 | 25 | 80 |
2023 Janeiro | 19 | 18 | 37 |
2022 Dezembro | 64 | 20 | 84 |
2022 Novembro | 60 | 28 | 88 |
2022 Outubro | 29 | 16 | 45 |
2022 Setembro | 28 | 39 | 67 |
2022 Agosto | 44 | 26 | 70 |
2022 Julho | 36 | 35 | 71 |
2022 Junho | 16 | 25 | 41 |
2022 Maio | 39 | 34 | 73 |
2022 Abril | 26 | 22 | 48 |
2022 Maro | 32 | 29 | 61 |
2022 Fevereiro | 33 | 51 | 84 |
2022 Janeiro | 24 | 27 | 51 |
2021 Dezembro | 32 | 27 | 59 |
2021 Novembro | 28 | 40 | 68 |
2021 Outubro | 27 | 40 | 67 |
2021 Setembro | 27 | 31 | 58 |
2021 Agosto | 29 | 38 | 67 |
2021 Julho | 23 | 32 | 55 |
2021 Junho | 24 | 25 | 49 |
2021 Maio | 25 | 35 | 60 |
2021 Abril | 53 | 36 | 89 |
2021 Maro | 49 | 24 | 73 |
2021 Fevereiro | 55 | 24 | 79 |
2021 Janeiro | 48 | 11 | 59 |
2020 Dezembro | 25 | 5 | 30 |
2020 Novembro | 25 | 15 | 40 |
2020 Outubro | 29 | 18 | 47 |
2020 Setembro | 56 | 14 | 70 |
2020 Agosto | 21 | 11 | 32 |
2020 Julho | 50 | 12 | 62 |
2020 Junho | 51 | 14 | 65 |
2020 Maio | 27 | 18 | 45 |
2020 Abril | 50 | 18 | 68 |
2020 Maro | 29 | 8 | 37 |
2020 Fevereiro | 58 | 30 | 88 |
2020 Janeiro | 19 | 17 | 36 |
2019 Dezembro | 50 | 7 | 57 |
2019 Novembro | 45 | 11 | 56 |
2019 Outubro | 56 | 5 | 61 |
2019 Setembro | 59 | 11 | 70 |
2019 Agosto | 31 | 15 | 46 |
2019 Julho | 27 | 12 | 39 |
2019 Junho | 24 | 12 | 36 |
2019 Maio | 32 | 16 | 48 |
2019 Abril | 22 | 9 | 31 |
2019 Maro | 45 | 11 | 56 |
2019 Fevereiro | 35 | 8 | 43 |
2019 Janeiro | 20 | 3 | 23 |
2018 Dezembro | 28 | 12 | 40 |
2018 Novembro | 53 | 6 | 59 |
2018 Outubro | 129 | 20 | 149 |
2018 Setembro | 17 | 9 | 26 |
2018 Agosto | 25 | 11 | 36 |
2018 Julho | 17 | 4 | 21 |
2018 Junho | 32 | 8 | 40 |
2018 Maio | 27 | 10 | 37 |
2018 Abril | 40 | 8 | 48 |
2018 Maro | 45 | 10 | 55 |
2018 Fevereiro | 27 | 12 | 39 |
2018 Janeiro | 34 | 9 | 43 |
2017 Dezembro | 55 | 13 | 68 |
2017 Novembro | 56 | 16 | 72 |
2017 Outubro | 29 | 23 | 52 |
2017 Setembro | 27 | 11 | 38 |
2017 Agosto | 38 | 14 | 52 |
2017 Julho | 33 | 13 | 46 |
2017 Junho | 40 | 20 | 60 |
2017 Maio | 61 | 23 | 84 |
2017 Abril | 35 | 17 | 52 |
2017 Maro | 44 | 20 | 64 |
2017 Fevereiro | 72 | 48 | 120 |