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ateromatosa y renal ocultas y su impacto en la morbimortalidad: Proyecto ILERVAS" ] ] "contieneResumen" => array:2 [ "en" => true "es" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0015" "etiqueta" => "Fig. 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 1789 "Ancho" => 2503 "Tamanyo" => 395058 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Population selection diagram for the ILERVAS project. <span class="elsevierStyleSup">a</span> Randomised by cluster (CAP) annually. CAP: primary care centre; CV: cardiovascular; CKD: chronic kidney disease; CVRF: cardiovascular risk factor; MU: mobile unit.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Àngels Betriu, Cristina Farràs, María Abajo, Montserrat Martinez-Alonso, David Arroyo, Ferran Barbé, Miquel Buti, Albert Lecube, Manuel Portero, Francisco Purroy, Gerard Torres, José Manuel Valdivielso, Elvira Fernández" "autores" => array:13 [ 0 => array:2 [ "nombre" => "Àngels" "apellidos" => "Betriu" ] 1 => array:2 [ "nombre" => "Cristina" "apellidos" => "Farràs" ] 2 => array:2 [ "nombre" => "María" "apellidos" => "Abajo" ] 3 => array:2 [ "nombre" => "Montserrat" "apellidos" => "Martinez-Alonso" ] 4 => array:2 [ "nombre" => "David" "apellidos" => "Arroyo" ] 5 => array:2 [ "nombre" => "Ferran" "apellidos" => "Barbé" ] 6 => array:2 [ "nombre" => "Miquel" "apellidos" => "Buti" ] 7 => array:2 [ "nombre" => "Albert" "apellidos" => "Lecube" ] 8 => array:2 [ "nombre" => "Manuel" "apellidos" => "Portero" ] 9 => array:2 [ "nombre" => "Francisco" "apellidos" => "Purroy" ] 10 => array:2 [ "nombre" => "Gerard" "apellidos" => "Torres" ] 11 => array:2 [ "nombre" => "José Manuel" "apellidos" => "Valdivielso" ] 12 => array:2 [ "nombre" => "Elvira" "apellidos" => "Fernández" ] ] ] ] ] "idiomaDefecto" => "en" "Traduccion" => array:1 [ "es" => array:9 [ "pii" => "S0211699516000382" "doi" => "10.1016/j.nefro.2016.02.008" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "es" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0211699516000382?idApp=UINPBA000064" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2013251416300682?idApp=UINPBA000064" "url" => "/20132514/0000003600000004/v1_201612030031/S2013251416300682/v1_201612030031/en/main.assets" ] "en" => array:21 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "The neutrophil–lymphocyte ratio as a marker of systemic endothelial dysfunction in asymptomatic subjects" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "397" "paginaFinal" => "403" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Diego Martínez-Urbistondo, Almudena Beltrán, Oscar Beloqui, Ana Huerta" "autores" => array:4 [ 0 => array:2 [ "nombre" => "Diego" "apellidos" => "Martínez-Urbistondo" ] 1 => array:2 [ "nombre" => "Almudena" "apellidos" => "Beltrán" ] 2 => array:2 [ "nombre" => "Oscar" "apellidos" => "Beloqui" ] 3 => array:4 [ "nombre" => "Ana" "apellidos" => "Huerta" "email" => array:1 [ 0 => "ahuerta@unav.es" ] "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] ] "afiliaciones" => array:1 [ 0 => array:2 [ "entidad" => "Departamento de Medicina Interna, Clínica Universidad de Navarra, Pamplona, Navarra, Spain" "identificador" => "aff0005" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "<span class="elsevierStyleItalic">Corresponding author</span>." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "El índice neutrófilo/linfocito como marcador de disfunción sistémica endotelial en sujetos asintomáticos" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1145 "Ancho" => 1369 "Tamanyo" => 60853 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Distribution of abnormal UACR in different NLR groups. UACR, urinary albumin/creatinine ratio; NLR, neutrophil–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">Each year, cardiovascular diseases (CVDs) cause around 4<span class="elsevierStyleHsp" style=""></span>million deaths in Europe and 1.9<span class="elsevierStyleHsp" style=""></span>million deaths in the European Union, accounting for 47% of all deaths in Europe and 40% of all deaths in the European Union. CVDs are the most common cause of death in women in all European countries and the most common cause of death in men in at least 6 of them. CVDs cost €196,000<span class="elsevierStyleHsp" style=""></span>million each year in Europe (54% in healthcare spending, 24% in lost productivity and 22% in the care of patients with CVD).<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">1</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">The high prevalence of cardiovascular risk factors, especially smoking, obesity and diabetes, promotes the development of CVDs, and therefore detection and management of cardiovascular risk factors is very important. The World Health Organisation believes that 75% of deaths due to CVDs could be prevented with suitable changes in lifestyle and modification of risk factors.<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">2</span></a> Therefore, early detection of patients with cardiovascular risk is an objective of major importance. To this end, an abnormal urinary albumin/creatinine ratio (UACR) has been shown to be an early marker of cardiovascular morbidity and mortality.<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">3</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Noteworthy among the mechanisms involved between an abnormal UACR and CVDs is endothelial dysfunction, at both the microvascular level (decrease in nitric oxide, increase in von Willebrand factor, vascular endothelial growth factor, asymmetric dimethylarginine [ADMA]) and the macrovascular level (vessel dilatation).<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">4</span></a> This damage is due in part to inflammation of the endothelium of the microvasculature, which promotes the accumulation of lipids and the development of atherosclerosis.<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">5</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">Inflammation plays a central role in the physiopathology of diseases that are considered to be non-inflammatory, such as cancer and atherosclerosis.<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">6–11</span></a> The determination of circulating peripheral blood leukocytes is a simple, inexpensive and widely available method that helps to assess inflammation. Among the various leucocyte parameters, the ratio absolute neutrophil count to the absolute lymphocyte count (neutrophil–lymphocyte ratio [NLR]) is significantly associated to elevation pro-inflammatory cytokine concentration and development of CVD and progression.<a class="elsevierStyleCrossRefs" href="#bib0245"><span class="elsevierStyleSup">12–14</span></a> This parameter has been shown to be an inflammatory marker with a high predictive power of death, acute myocardial infarction and severity of coronary heart disease.<a class="elsevierStyleCrossRefs" href="#bib0255"><span class="elsevierStyleSup">14–16</span></a> In addition, various studies have investigated the link between NLR and diabetes mellitus, insulin resistance as assessed by the Homoeostasis Model Assessment of Insulin Resistance (HOMA-IR), hypertension, obesity, hyperlipidaemia, lifestyle and endothelial dysfunction.<a class="elsevierStyleCrossRefs" href="#bib0270"><span class="elsevierStyleSup">17–19</span></a></p><p id="par0025" class="elsevierStylePara elsevierViewall">To date, studies about the association between NLR and CVDs have been performed in patients with symptomatic CVD. The objective of this study was to evaluate whether this association is observed in asymptomatic subjects without a prior history of CVD, using an abnormal UACR as an early marker of systemic endothelial damage and cardiovascular risk.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Materials and methods</span><p id="par0030" class="elsevierStylePara elsevierViewall">A cross-sectional study was conducted with patients from several regions of Spain who visited the Clínica Universidad de Navarra for routine medical check-up and an estimation of cardiovascular risk. A total of 2246 clinically asymptomatic patients were evaluated since May 1999–January 2011. Each patient underwent a complete medical history that included the collection of family histories of CVD, as well as general laboratory testing with a complete blood count, blood chemistry, cholesterol fractions and the determination of albumin and creatinine in urine from first urination. Patients were excluded if they had a personal history of cardiovascular events (acute myocardial infarction, stroke or peripheral artery disease), were on antiproteinuric drugs (angiotensin converting enzyme inhibitors and angiotensin II receptor antagonists) or had a UACR >300<span class="elsevierStyleHsp" style=""></span>mg/g. The 1816 remaining subjects were enrolled in the final cohort. The study was designed in accordance with the Declaration of Helsinki and the protocol was approved by the Clínica Universidad de Navarra Ethics Committee.</p><p id="par0035" class="elsevierStylePara elsevierViewall">Cardiovascular risk factors were defined according to the guidelines of the modified Adult Treatment Panel (ATP)-III.<a class="elsevierStyleCrossRef" href="#bib0285"><span class="elsevierStyleSup">20</span></a> Laboratory determinations were made using standard laboratory techniques. To calculate the NLR, the ratio absolute neutrophil count to absolute lymphocyte count was obtained from the complete blood count. To evaluate insulin resistance, the HOMA-IR was used as both a continuous variable and as values above or below the cut-off point of 2.<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">19</span></a> The Modification of Diet in Renal Disease formula was used for the estimated glomerular filtration rate (eGFR),, and it was considered to be pathological below 60<span class="elsevierStyleHsp" style=""></span>ml/min/1.73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span>. A urinary albumin/creatinine ratio between 30 and 300<span class="elsevierStyleHsp" style=""></span>mg/g was used as a marker of endothelial dysfunction and cardiovascular risk.<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">21</span></a></p><p id="par0040" class="elsevierStylePara elsevierViewall">The results were expressed as the value of the arithmetic mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>standard deviation for continuous quantitative variables. Qualitative variables were presented in the form of proportions. Univariate statistical analysis was performed using hypothesis-corroborating tests: the chi-squared test for qualitative variables, Student's t test for comparisons of quantitative variables with homogeneity of variances in Levene's test and the Mann–Whitney <span class="elsevierStyleItalic">U</span> test in the rest. Multivariate analysis was performed using logistic regression models. A sensitivity analysis was performed to seek the values with the greatest discriminatory capacity. In the results of this analysis, the parameters with the highest sensitivity and specificity were considered to be clinically useful.<a class="elsevierStyleCrossRef" href="#bib0295"><span class="elsevierStyleSup">22</span></a> Statistical calculations were performed using the SPSS version 20.0 program.</p></span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Results</span><p id="par0045" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> shows the clinical characteristics of the study population. Mean NLR was 2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.83. Abnormal UACR was observed in 7.5% of patients.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0050" class="elsevierStylePara elsevierViewall">As shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>, abnormal UACR was significantly associated with age, obesity, hypertension, diabetes, insulin resistance (HOMA-IR<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>2), dyslipidaemia and <60<span class="elsevierStyleHsp" style=""></span>ml/min/1.73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span> of eGFR. The same table shows a significant increase in NLR in patients with an abnormal UACR. C-reactive protein (CRP) was used to evaluate an abnormal UACR's capacity for predicting other markers of inflammation. This analysis was performed in a subgroup of the patients in which this determination was available (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>439). In this subgroup, the prevalence of an abnormal UACR was 8%, which was similar to that of the general population (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>0.5). No statistically significant differences were found in CRP levels in patients with an abnormal UACR as compared with a UACR within normal limits (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.45). Nevertheless, in this subgroup of 439 patients, NLR remained significantly associated with an abnormal UACR (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05).</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0055" class="elsevierStylePara elsevierViewall">After the univariate analysis, a logistic regression model was prepared including all the previously significant variables. As shown in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>, all the vascular risk factors except obesity remained significantly and independently associated with an abnormal UACR. The NLR value remained an independent marker of an abnormal UACR (OR: 1.45. <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.01). In an alternative model, the HOMA-IR was changed by diabetes to avoid collinearity. The HOMA-IR was significant in identifying an abnormal UACR (OR: 1.11; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.01), and the predictive power of NLR's persisted. Table complementary 1 presents this model. In the subgroup of 439 patients whose CRP levels were available, 2 multivariate models were tested with the same adjustment variables. The first model used the NLR to predict inflammation; it was significantly associated with an abnormal UACR (OR: 1.6; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.01; Table complementary 2). By contrast, the second model that used CRP as a marker of inflammation, it was not significantly associated with an abnormal UACR (OR: 0.94; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>0.05; Table complementary 3).</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0060" class="elsevierStylePara elsevierViewall">Subsequently, the relationship between the NLR and the different cardiovascular risk factors was studied. In our study, hypertension, diabetes, smoking and obesity were not associated with the NLR. Moreover, the anti-inflammatory effect of statins on the endothelium could affect the relationship between the NLR and an abnormal UACR.<a class="elsevierStyleCrossRefs" href="#bib0300"><span class="elsevierStyleSup">23,24</span></a> In our series, the 196 patients being treated with statins had lower NLR values, although the difference was not statistically significant, (1.89<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.85 for the group with statins vs 2.01<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.83 for the group without statins, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>0.05). However, statistically significant differences were observed between the NLR of patients with a HOMA-IR<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>2, as compared to patients without insulin resistance (1.94<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.78 vs 2.05<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.89 <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05).</p><p id="par0065" class="elsevierStylePara elsevierViewall">Next, the distribution of the NLR in our sample was analysed. To do this, the population was divided into 2 groups depending on whether or not they had an abnormal UACR. Then, patients in both subgroups were divided into 11 NLR strata, each spanning 0.5 units, from an NLR of 0–0.5 to an NLR of >5. As shown in <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>, 87.1% of the population had NLR levels between 1 and 3. Moreover, starting from an NLR value >2.5, the relative proportion of patients with an abnormal UACR clearly increased.</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0070" class="elsevierStylePara elsevierViewall">After these results were obtained, the NLR cut-off point with the greatest abnormal UACR discriminatory capacity was estimated by using a sensitivity analysis. To do this, the sensitivity, specificity, positive predictive values and negative predictive values were calculated for NLR values between 1.5 and 3. The results can be seen in <a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>. The table shows that the lowest NLR values had greater sensitivity for detecting abnormal UACRs, while higher NLR values had greater specificity. The results of this analysis defined the values of 1.5 and 3 as cut-off points for the risk subgroups, given the greater sensitivity of the former and the greater specificity of the latter. The population was divided into 3 groups of patients at risk of an abnormal UACR depending on the NLR: low risk (NLR<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>1.5), intermediate risk (NLR between 1.5 and 3) and high risk (NLR<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>3). <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a> shows the distribution of abnormal UACRs in the 3 groups. It should be noted that the relative proportion of abnormal UACRs progressively and significantly increased as NLR values increased.</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall">Finally, the cut-off points for the risk subgroups were included in a multivariate model that is shown in <a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>. Patients with an NLR between 1.5 and 3 had an OR of 1.68 as compared to those with an NLR<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>1.5. Patients with an NLR<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>3 had an increased risk up to an OR of 3.14 in the same comparison. This new model, which had a significant discrimination improvement rate (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.01), with a reclassification improvement rate of 4.05%, was subsequently analysed. This result would implicate the reclassification of 74 patients in the sample.</p><elsevierMultimedia ident="tbl0025"></elsevierMultimedia></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Discussion</span><p id="par0080" class="elsevierStylePara elsevierViewall">Inflammation plays a fundamental role in the pathophysiology of CVDs.<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">6</span></a> Among the various markers of inflammation, the NLR has been previously assessed as a predictor of mortality in patients with acute coronary syndrome,<a class="elsevierStyleCrossRef" href="#bib0310"><span class="elsevierStyleSup">25</span></a> congestive heart failure<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">26</span></a> and diabetes mellitus<a class="elsevierStyleCrossRef" href="#bib0320"><span class="elsevierStyleSup">27</span></a> and patients having undergone a coronary catheterisation.<a class="elsevierStyleCrossRef" href="#bib0325"><span class="elsevierStyleSup">28</span></a> In addition, it has recently been evaluated as a risk factor in a study of asymptomatic patients in the cohort from Framingham's study, which confirmed to be a powerful predictor of cardiovascular mortality. This study refers NLR as a parameter with a potential cardiovascular risk reclassification capacity that is greater than other markers such as ultrasensitive CRP, the N-terminal fragment of the B-type natriuretic peptide, glycated haemoglobin, cystatin and homocysteine.<a class="elsevierStyleCrossRef" href="#bib0330"><span class="elsevierStyleSup">29</span></a></p><p id="par0085" class="elsevierStylePara elsevierViewall">Previous publications have reported an association between NLR values and urinary albumin excretion, in both diabetic patients<a class="elsevierStyleCrossRef" href="#bib0335"><span class="elsevierStyleSup">30</span></a> and patients with symptomatic chronic kidney disease.<a class="elsevierStyleCrossRef" href="#bib0340"><span class="elsevierStyleSup">31</span></a> The importance of detecting the mechanisms of endothelial damage to prevent CVD justifies the use of an abnormal UACR as an early marker of both cardiovascular risk and systemic endothelial dysfunction.<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">5,32–35</span></a> In this study's cohort, a clinically asymptomatic patient population, the NLR was also significantly correlated with an abnormal UACR. This association was present regardless of other risk factors associated with an abnormal UACR.</p><p id="par0090" class="elsevierStylePara elsevierViewall">Several studies have associated inflammation with greater insulin resistance.<a class="elsevierStyleCrossRef" href="#bib0365"><span class="elsevierStyleSup">36</span></a> Recently, Lou et al.<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">19</span></a> presented a significant correlation between an increase in the NLR and the HOMA-IR (OR: 7.23 <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.01). The association between insulin resistance and the NLR was confirmed in our sample. The anti-inflammatory effect of HMG-CoA reductase inhibitors could also have an influence on the NLR.<a class="elsevierStyleCrossRefs" href="#bib0300"><span class="elsevierStyleSup">23,24</span></a> However, an article by Gungoren et al.<a class="elsevierStyleCrossRef" href="#bib0370"><span class="elsevierStyleSup">37</span></a> demonstrated no statistically significant differences in NLR among patients treated with statins and patients not treated with statins. In our analysis, patients on statins had a low NLR without statistical differences between the groups. Our results may justify the study of this association in cohorts with a larger number of patients. Finally, our results showed that as compared with CRP, the NLR has a greater capacity to detect an abnormal UACR. In fact CRP did no show statistically significance in this context.</p><p id="par0095" class="elsevierStylePara elsevierViewall">A useful risk marker requires to know what are the levels with clinically significance These levels can be properly selected using a sensitivity and specificity analysis of different cut-off points of the marker in question. This methodology has been extensively studied and used in selecting cut-off points in other clinical situations.<a class="elsevierStyleCrossRef" href="#bib0295"><span class="elsevierStyleSup">22</span></a> Noteworthy in our study was the limited sensitivity that all the levels offered, except the cut-off point of 1.5, which had a sensitivity of 0.80. Sensitivity is the result of the ratio between the true positives in a test and the sick patients in the population. A low sensitivity is related to an increase in the false negatives in the test. As the classic risk factors for an abnormal UACR were not found to be associated with the NLR in our sample, many patients would have been false negatives if had only the NLR had been considered. However, statistically significant differences between the NLR groups in the multivariate analysis validated the usefulness of the cut-off points selected using this method.</p><p id="par0100" class="elsevierStylePara elsevierViewall">The main limitation of our study was its cross-sectional design, which prevented the establishment of a causal relationship between the NLR and an abnormal UACR. Moreover, although the population recruited from a single centre limited extrapolation of the results, the sample size and the fact that the patients were from different regions of Spain increased the study's external validity. In any case, the association between the NLR and an abnormal UACR deserves to be studied in greater depth to determine its role not only as an inexpensive, quick and non-invasive marker of cardiovascular risk but also as a potential therapeutic target.</p><p id="par0105" class="elsevierStylePara elsevierViewall">This study demonstrated a significant correlation between, clinically significant NLR values and cardiovascular risk and systemic endothelial dysfunction associated to microvascular disease in a cohort of asymptomatic patients. Given the limitations set forth above, interventional, multi-centre studies with a greater number of outcomes are required to assess other potential clinical implications of this finding.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Conclusion</span><p id="par0110" class="elsevierStylePara elsevierViewall">The NLR may represent a new tool for the assessment of cardiovascular risk and the risk of systemic endothelial dysfunction associated with microvascular disease in asymptomatic patients.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Funding</span><p id="par0115" class="elsevierStylePara elsevierViewall">The study required no external funding.</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Conflicts of interest</span><p id="par0120" 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" => "xres767396" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background and objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Materials and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec768545" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres767397" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Fundamento y objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Materiales y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec768546" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:2 [ "identificador" => "sec0010" "titulo" => "Materials and methods" ] 6 => array:2 [ "identificador" => "sec0015" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0020" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0025" "titulo" => "Conclusion" ] 9 => array:2 [ "identificador" => "sec0030" "titulo" => "Funding" ] 10 => array:2 [ "identificador" => "sec0035" "titulo" => "Conflicts of interest" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2015-07-02" "fechaAceptado" => "2015-10-28" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec768545" "palabras" => array:5 [ 0 => "Neutrophil–lymphocyte ratio" 1 => "Urinary albumin/creatinine ratio" 2 => "Endothelial dysfunction" 3 => "Cardiovascular risk" 4 => "Asymptomatic subjects" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec768546" "palabras" => array:5 [ 0 => "Índice neutrófilo/linfocito" 1 => "Cociente albúmina/creatinina urinario" 2 => "Disfunción endotelial" 3 => "Riesgo cardiovascular" 4 => "Sujetos asintomáticos" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background and objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">The neutrophil-to-lymphocyte ratio has demonstrated to be a prognostic inflammatory marker in cardiovascular disease. The objective of this study is to evaluate the association between neutrophil–lymphocyte ratio and pathologic urinary albumin/creatinine ratio as an early marker of cardiovascular risk and systemic endothelial dysfunction, associated with microvascular disease, in asymptomatic subjects.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Materials and methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">A unicenter cross-sectional study was conducted, including 1816 asymptomatic subjects. Patients with previous cardiovascular disease, those who were treated with ACE inhibitors and/or angiotensin II receptor blockers and patients with albumin/creatinine ratio over 300<span class="elsevierStyleHsp" style=""></span>mg/g were excluded. The outcome of the study was the presence of a pathologic urinary albumin/creatinine ratio.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The neutrophil–lymphocyte ratio was significantly associated with altered urinary albumin/creatinine ratio in the univariate analysis and after adjustment for other known endothelial and cardiovascular risk factors (age, hypertension, dyslipidaemia, diabetes or altered glomerular filtration rate). Based on the sensitivity and specificity of different neutrophil–lymphocyte ratio thresholds, 3 risk groups were created for altered urinary albumin/creatinine ratio: low risk in those with neutrophil–lymphocyte ratio <1.5, intermediate risk in patients between 1.5 and 3, and high risk in those with neutrophil- to-lymphocyte ratio >3. These groups were found to have a statistically significant and independent prognostic power for altered urinary albumin/creatinine ratio in asymptomatic patients.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">The neutrophil–lymphocyte ratio appears to be a cost-efficient, non-invasive and independent potential marker of systemic endothelial dysfunction in asymptomatic subjects.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background and objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Materials and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Fundamento y objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">El índice neutrófilo/linfocito es un marcador inflamatorio devalor pronóstico en enfermedades cardiovasculares. El objetivo del presente trabajo esvalorar la asociación entre el índice neutrófilo/linfocito y la alteración del cociente albú-mina/creatinina urinario como marcador precoz de disfunción endotelial sistémica asociadaa enfermedad microvascular y riesgo cardiovascular, en sujetos asintomáticos.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Materiales y métodos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Se realizó un estudio transversal en 1.816 sujetos asintomáticos. Seexcluyó del a estudio aquellos pacientes que presentaron antecedentes de enfermedad car-diovascular, los que recibían tratamiento con fármacos antiproteinúricos (inhibidores de laenzima conversora de angiotensina y antagonistas de los receptores de la angiotensina II) yaquellos que presentaron un cociente albúmina/creatinina superior a 300<span class="elsevierStyleHsp" style=""></span>mg/dL. La variabledesenlace del estudio fue la alteración del cociente albúmina/creatinina urinario.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">El índice neutrófilo/linfocito resultó significativamente asociado a la alteracióndel cociente albúmina/creatinina urinario, tanto en el estudio univariante como en el mul-tivariante, independientemente de otros cofactores como la edad, la hipertensión arterial,la diabetes, la dislipidemia o el filtrado glomerular patológico. El análisis de la sensibilidad yla especificidad de distintos niveles del índice neutrófilo/linfocito permitió generar 3 gruposde riesgo de alteración del cociente albúmina/creatina urinario: riesgo bajo con un cocienteneutrófilo/linfocito < 1,5, riesgo intermedio con cociente neutrófilo/linfocito entre 1,5 y 3 yriesgo alto con un cociente neutrófilo/linfocito > 3. La proporción relativa de alteración delcociente albúmina/creatinina urinario, en los 3 grupos de riesgo, aumentaba en razón delvalor del índice neutrófilo/linfocito de forma independiente al resto de cofactores.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">El índice neutrófilo/linfocito surge como un potencial marcador de disfun-ción endotelial sistémica económico, rápido, no invasivo e independiente de otros factoresconocidos, en sujetos asintomáticos.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Fundamento y objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Materiales y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0015">Please cite this article as: Martínez-Urbistondo D, Beltrán A, Beloqui O, Huerta A. El índice neutrófilo/linfocito como marcador de disfunción sistémica endotelial en sujetos asintomáticos. Nefrologia. 2016;36:397–403.</p>" ] ] "apendice" => array:1 [ 0 => array:1 [ "seccion" => array:1 [ 0 => array:4 [ "apendice" => "<p id="par0130" class="elsevierStylePara elsevierViewall">The following are the supplementary data to this article:<elsevierMultimedia ident="upi0005"></elsevierMultimedia></p>" "etiqueta" => "Appendix A" "titulo" => "Supplementary data" "identificador" => "sec0045" ] ] ] ] "multimedia" => array:8 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 850 "Ancho" => 1614 "Tamanyo" => 78830 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Distribution of abnormal UACR according to NLR level. UACR, urinary albumin/creatinine ratio; NLR, neutrophil–lymphocyte ratio.</p>" ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1145 "Ancho" => 1369 "Tamanyo" => 60853 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Distribution of abnormal UACR in different NLR groups. UACR, urinary albumin/creatinine ratio; NLR, neutrophil–lymphocyte ratio.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">UACR, urinary albumin/creatinine ratio; CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate; HDL, high-density lipoprotein; HOMA-IR, Homeostatic Model Assessment of Insulin Resistance; BMI, body mass index; NLR, neutrophil–lymphocyte ratio; LDL, low density lipoprotein.</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 " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Characteristic</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">Family history of CVD (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">174 (9.6) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><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="left" valign="top">52.89<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>10.94 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top"><span class="elsevierStyleItalic">Age quartiles (range of years)</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>Quartile 1 (18–45) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">38.91<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.24 \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>Quartile 2 (46–53) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">49.74<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Quartile 3 (54–60) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">56.95<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>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"><span class="elsevierStyleHsp" style=""></span>Quartile 4 (61–87) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">66.98<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.24 \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">Males (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1386 (76.3) \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><span class="elsevierStyleItalic">)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">27.94<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.22 \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 (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">478 (26.3) \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">Systolic blood pressure (mmHg)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">124.01<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>19.29 \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">Diastolic blood pressure (mmHg)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">79.59<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.51 \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">Glucose (mg/dl)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">100.44<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>26.13 \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">HOMA-IR (μU·mmol/l</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">2</span></span><span class="elsevierStyleItalic">)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.63<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>2.36 \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">Insulin (μU/ml)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">10.45<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.66 \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">HDL (mg/dl)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">53.34<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>15.40 \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">LDL (mg/dl)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">142.77<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>38.08 \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"><span class="elsevierStyleItalic">Total cholesterol (mg/dl)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">219<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>41.09 \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"><span class="elsevierStyleItalic">Triglycerides (mg/dl)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">117.69<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>80.63 \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">Neutrophils (10</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">9</span></span><span class="elsevierStyleItalic">/l)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.66<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.31 \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">Lymphocytes (10</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">9</span></span><span class="elsevierStyleItalic">/l)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.93<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.56 \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">NLR</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.00<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.83 \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">C-reactive protein (mg/dl)</span><a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.49<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.04 \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">Creatinine (mg/dl)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.95<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.19 \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">eGFR (ml/min/1.73</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">m</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">2</span></span><span class="elsevierStyleItalic">)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">76<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Albumin/creatinine (mg/g)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">11.46<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>22.79 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Hypertension (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">612 (33.7) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Diabetes mellitus (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">249 (13.7) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Dyslipidaemia (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">934 (51.4) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Abnormal UACR (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">137 (7.5) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1269750.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">The results for a subgroup of 439 patients are included.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Clinical characteristics of the population (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1816).</p>" ] ] 3 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">UACR, urinary albumin/creatinine ratio; CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate; HOMA-IR, Homeostatic Model Assessment of Insulin Resistance; NLR, neutrophil–lymphocyte ratio.</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="center" valign="top" scope="col" style="border-bottom: 2px solid black">Normal UACR (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1679) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Abnormal UACR (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>137) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span> \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">Family history of CVD (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">158 (9.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">18 (13.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">NS \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 (years) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">52.46<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>10.82 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">58.12<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>11.15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \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">Males (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1275 (75.94) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">111 (81.02) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">NS \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">Obesity (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">437 (26.03) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">55 (40.15) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Smoking (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">435 (25.95) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">43 (31.42) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">NS \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">Hypertension (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">520 (31.06) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">92 (67.21) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \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">Type 2 diabetes mellitus (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">197 (11.72) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">52 (38.03) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \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">HOMA-IR<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>2 (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">689 (50.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">79 (73.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \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">Dyslipidaemia (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">842 (52.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">92 (72.46) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \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">Pathological eGFR (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">72 (4.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">18 (13.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \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">1.97<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.30<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \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">C-reactive protein (mg/dl)<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.56<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.50 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.49<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.90 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1269754.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0010">The results for a subgroup of 439 patients are included.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Univariate analysis of the association of different cardiovascular risk factors with an abnormal UACR.</p>" ] ] 4 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at3" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">eGFR, estimated glomerular filtration rate; NLR, neutrophil–lymphocyte ratio; OR, odds ratio.</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="left" valign="top" scope="col" style="border-bottom: 2px solid black">Variable \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">OR (95% CI) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span> \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">1.03 (1.01–1.05) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.01 \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">Obesity \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.30 (0.86–1.97) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">NS \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">Hypertension \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.28 (2.12–5.04) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Diabetes mellitus \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.40 (2.17–5.32) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \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">Dyslipidaemia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.22 (1.44–3.43) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \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">Pathological eGFR \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.87 (1.52–5.41) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \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 (per unit) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.45 (1.20–1.74) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1269751.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Multivariate analysis of the association of different cardiovascular risk factors with an abnormal UACR.</p>" ] ] 5 => array:8 [ "identificador" => "tbl0020" "etiqueta" => "Table 4" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at4" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">NLR, neutrophil–lymphocyte ratio; NPV, negative predictive value; PPV, positive predictive value.</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="center" valign="top" scope="col" style="border-bottom: 2px solid black">NLR<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>1.5 \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">NLR<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>2 \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">NLR<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>2.5 \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">NLR<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>3 \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">Sensitivity \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.18 \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">Specificity \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.29 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.82 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.91 \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">PPV \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><td class="td" title="table-entry " align="char" valign="top">0.09 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.14 \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">NPV \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.95 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.93 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.93 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1269753.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">Analysis of sensitivity of the NLR in the prediction of an abnormal UACR.</p>" ] ] 6 => 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="spar0100" class="elsevierStyleSimplePara elsevierViewall">eGFR, estimated glomerular filtration rate; NLR, neutrophil–lymphocyte ratio; OR, odds ratio.</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="left" valign="top" scope="col" style="border-bottom: 2px solid black">Variable \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">OR (95% CI) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span> \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</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.03 (1.01–1.05) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.01 \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">Obesity</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.29 (0.85–1.95) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">NS \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">Hypertension</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.32 (2.16–5.11) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \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 mellitus</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.51 (2.25–5.49) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \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">Dyslipidaemia</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.18 (1.42–3.35) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \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">Pathological eGFR</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.86 (1.51–5.41) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="3" 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="3" align="left" valign="top"><span class="elsevierStyleItalic">Neutrophil–lymphocyte ratio</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>NLR 1.5–3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Comparator \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.01 \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>NLR 1.5–3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.68 (1.03–2.76) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.03 \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>NLR<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.14 (1.63–6.04) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1269752.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">Multivariate analysis of vascular risk factors and different cut-off points of the NLR in relation to an abnormal UACR.</p>" ] ] 7 => array:5 [ "identificador" => "upi0005" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => false "mostrarDisplay" => true "Ecomponente" => array:2 [ "fichero" => "mmc1.docx" "ficheroTamanyo" => 13986 ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:37 [ 0 => array:3 [ "identificador" => "bib0190" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "European cardiovascular disease statistics" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M. 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Year/Month | Html | Total | |
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2024 July | 95 | 26 | 121 |
2024 June | 74 | 33 | 107 |
2024 May | 78 | 44 | 122 |
2024 April | 78 | 34 | 112 |
2024 March | 64 | 24 | 88 |
2024 February | 53 | 33 | 86 |
2024 January | 48 | 26 | 74 |
2023 December | 37 | 18 | 55 |
2023 November | 96 | 29 | 125 |
2023 October | 85 | 25 | 110 |
2023 September | 52 | 30 | 82 |
2023 August | 42 | 25 | 67 |
2023 July | 55 | 27 | 82 |
2023 June | 51 | 16 | 67 |
2023 May | 68 | 32 | 100 |
2023 April | 49 | 10 | 59 |
2023 March | 79 | 19 | 98 |
2023 February | 61 | 22 | 83 |
2023 January | 53 | 19 | 72 |
2022 December | 71 | 32 | 103 |
2022 November | 85 | 27 | 112 |
2022 October | 82 | 38 | 120 |
2022 September | 61 | 33 | 94 |
2022 August | 70 | 38 | 108 |
2022 July | 57 | 52 | 109 |
2022 June | 51 | 34 | 85 |
2022 May | 76 | 37 | 113 |
2022 April | 89 | 42 | 131 |
2022 March | 97 | 43 | 140 |
2022 February | 79 | 34 | 113 |
2022 January | 90 | 39 | 129 |
2021 December | 76 | 42 | 118 |
2021 November | 73 | 49 | 122 |
2021 October | 106 | 43 | 149 |
2021 September | 105 | 49 | 154 |
2021 August | 133 | 58 | 191 |
2021 July | 114 | 43 | 157 |
2021 June | 68 | 32 | 100 |
2021 May | 97 | 44 | 141 |
2021 April | 191 | 52 | 243 |
2021 March | 96 | 49 | 145 |
2021 February | 64 | 24 | 88 |
2021 January | 78 | 42 | 120 |
2020 December | 69 | 34 | 103 |
2020 November | 83 | 18 | 101 |
2020 October | 58 | 20 | 78 |
2020 September | 62 | 25 | 87 |
2020 August | 82 | 18 | 100 |
2020 July | 97 | 25 | 122 |
2020 June | 88 | 33 | 121 |
2020 May | 98 | 19 | 117 |
2020 April | 101 | 26 | 127 |
2020 March | 120 | 12 | 132 |
2020 February | 97 | 39 | 136 |
2020 January | 86 | 24 | 110 |
2019 December | 105 | 33 | 138 |
2019 November | 70 | 28 | 98 |
2019 October | 569 | 19 | 588 |
2019 September | 85 | 29 | 114 |
2019 August | 59 | 30 | 89 |
2019 July | 63 | 27 | 90 |
2019 June | 71 | 36 | 107 |
2019 May | 70 | 34 | 104 |
2019 April | 111 | 36 | 147 |
2019 March | 70 | 33 | 103 |
2019 February | 44 | 22 | 66 |
2019 January | 56 | 29 | 85 |
2018 December | 227 | 41 | 268 |
2018 November | 401 | 28 | 429 |
2018 October | 276 | 26 | 302 |
2018 September | 120 | 19 | 139 |
2018 August | 54 | 22 | 76 |
2018 July | 55 | 28 | 83 |
2018 June | 60 | 24 | 84 |
2018 May | 127 | 21 | 148 |
2018 April | 134 | 15 | 149 |
2018 March | 114 | 13 | 127 |
2018 February | 132 | 13 | 145 |
2018 January | 139 | 12 | 151 |
2017 December | 121 | 11 | 132 |
2017 November | 106 | 19 | 125 |
2017 October | 38 | 12 | 50 |
2017 September | 36 | 23 | 59 |
2017 August | 41 | 30 | 71 |
2017 July | 30 | 20 | 50 |
2017 June | 42 | 17 | 59 |
2017 May | 37 | 11 | 48 |
2017 April | 33 | 8 | 41 |
2017 March | 22 | 6 | 28 |
2017 February | 20 | 7 | 27 |
2017 January | 12 | 4 | 16 |
2016 December | 39 | 10 | 49 |
2016 November | 15 | 5 | 20 |