Epicardial adipose tissue thickness in children and adolescents with cardiometabolic risk factors | Endocrinología y Nutrición (English Edition)

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"apellidos" => "Lima-Martínez" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "d" "identificador" => "aff0020" ] ] ] ] "afiliaciones" => array:4 [ 0 => array:3 [ "entidad" => "Unidad de Endocrinología, Instituto Autónomo Hospital Universitario de los Andes, Mérida, Venezuela" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Unidad de Nutrición, Crecimiento y Desarrollo Infantil, Instituto Autónomo Hospital Universitario de los Andes, Mérida, Venezuela" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Instituto de Investigaciones Cardiovasculares, Instituto Autónomo Hospital Universitario de los Andes, Mérida, Venezuela" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Departamento de Ciencias Fisiológicas, Universidad de Oriente, Núcleo Bolívar, Ciudad Bolívar, Venezuela" "etiqueta" => "d" "identificador" => "aff0020" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Espesor del tejido adiposo epicárdico en niños y adolescentes con factores de riesgo cardiometabólico" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1048 "Ancho" => 2601 "Tamanyo" => 140633 ] ] "descripcion" => array:1 [ "en" => "ROC for establishing the cut-off point of EAT thickness for predicting two or more CRFs in this sample of children and adolescents." ] ] ] "textoCompleto" => "IntroductionDifferent studies have shown that obesity, together with other cardiometabolic risk factors (CRFs), is associated with subclinical markers of atherosclerosis in children and adolescents,<a class="elsevierStyleCrossRefs" href="#bib0150">1,2</a> and with early mortality in adulthood.<a class="elsevierStyleCrossRefs" href="#bib0160">3,4</a>Interest in organ-specific adiposity has increased rapidly in recent years. In this context, epicardial adipose tissue (EAT), the visceral fat of the heart, has emerged as a new cardiometabolic risk marker because of its close anatomical proximity to the myocardium and coronary artery, its endocrine and metabolic properties, and its diagnostic and therapeutic value.<a class="elsevierStyleCrossRef" href="#bib0170">5</a>EAT thickness is consistently associated with metabolic syndrome (MS) and its components,<a class="elsevierStyleCrossRefs" href="#bib0175">6,7</a> but changes markedly with age and between subjects from different ethnic groups, which has prevented agreement on a single general cut-off point for predicting the risk of MS.<a class="elsevierStyleCrossRefs" href="#bib0185">8,9</a> In Venezuela EAT thickness greater than 5mm was shown to have a good sensitivity and specificity for predicting MS<a class="elsevierStyleCrossRef" href="#bib0195">10</a>; that study, however, was conducted in an adult population, and its results are therefore not applicable to children and adolescents.A significant correlation has been shown in obese children between EAT thickness and other anthropometric variables such as the body mass index (BMI) and abdominal circumference (AC).<a class="elsevierStyleCrossRef" href="#bib0200">11</a> Kim et al.<a class="elsevierStyleCrossRef" href="#bib0205">12</a> similarly showed that EAT thickness measured by echocardiography is a practical and accurate marker of visceral obesity in adolescents. In fact, sedentary adolescents have been shown to have greater EAT thickness as compared to non-sedentary ones, and each 1-mm increase in EAT thickness increases sevenfold the risk of visceral obesity.<a class="elsevierStyleCrossRef" href="#bib0210">13</a>Recently, a 2.2% prevalence of MS has been reported in children and adolescents from Mérida, Venezuela; however, this population has a high frequency of abdominal obesity, hypertriglyceridemia, and high blood pressure.<a class="elsevierStyleCrossRef" href="#bib0215">14</a> No prior studies assessing EAT thickness in our children and adolescents are available. This study was therefore undertaken to assess EAT thickness in children and adolescents with CRFs, to ascertain to what extent our results were consistent with the few data available, and thus to make better use of the currently available diagnostic tools.Materials and methodsSubjectsThis was an observational, cross-sectional, analytical study. Participating subjects were selected from the outpatient clinics of endocrinology, nutrition, growth and pediatric development of the Instituto Autónomo Hospital Universitario de los Andes and the general population of Mérida, Venezuela. When sample size was considered, no studies were found comparing EAT thickness between children and adolescents, and estimation was therefore based on obese and non-obese data. Specifically, EAT thickness data from Mazur et al.<a class="elsevierStyleCrossRef" href="#bib0200">11</a> were used: 2.5±0.81mm for non-obese children and 5.5±1.98mm for obese children, with an α error of 0.05 and a β error of 0.20. The final sample size was 30 subjects per group. Overweight and obese subjects are known to have a greater frequency of CRFs than subjects with normal weight. Thus, overweight and obese individuals of both sexes aged 6–18 years of age were initially enrolled sequentially, and age- and sex-matched subjects with normal weight were subsequently selected to obtain comparable groups, which only differed in the number of CRFs. The participants came from different clinics and from the general population. Subjects with primary hyperlipidemia and endocrine diseases such as diabetes mellitus, hypothyroidism, and Cushing's syndrome, as well as any comorbidity or intake of drugs (glucocorticoids, lipid-lowering, antiepileptic) that could affect the tested variables were excluded from the study.The subjects were split into two groups based on the presence of CRFs: a control group consisting of subjects with less than two CRFs (no or one CRF) and a study group consisting of subjects with two or more CRFs. The CRFs considered included basal blood glucose≥100mg/dL (fasting hyperglycemia); AC>P90 (respective age and sex-abdominal obesity); systolic (SBP) and/or diastolic blood pressure (DBP)>P90 (respective age and sex-preHBP and HBP); triglycerides>P90 (respective age and sex-hypertriglyceridemia); HDL-C<P10 (respective age and sex-low HDL-C); and LDL-C>P90 (respective age and sex-hypercholesterolemia). The percentile distribution of the local population obtained in the CREDEFAR study was used as a reference.<a class="elsevierStyleCrossRefs" href="#bib0215">14,15</a> In compliance with ethical guidelines in the Declaration of Helsinki, only children and adolescents whose legal representative agreed to participation and signed the informed consent were enrolled into the study.ProcedureClinical evaluationWeight and height were measured under fasting conditions and with subjects in their underwear. The body mass index (BMI) was calculated as weight divided by squared height. Obesity was defined as a BMI>P97 for age and sex in the curves for Venezuelan children and adolescents prepared by FUNDACREDESA,<a class="elsevierStyleCrossRef" href="#bib0225">16</a> overweight as BMI values >P90 and ≤P97, normal weight as a BMI ranging from P10 to P90, and low weight as BMI<P10. The Z-score of the BMI was determined.<a class="elsevierStyleCrossRef" href="#bib0230">17</a> Abdominal circumference (AC) was measured in centimeters at the end of an expiration, with the subjects standing, at the level of the midline between the lower margin of the last rib and the iliac crest. Pubertal development was determined based on the Tanner stage in breast and pubic hair in girls, and in genitalia and pubic hair in boys. Subjects were considered prepubertal if they had no secondary sexual characteristics (Tanner I), while those with some secondary characteristics (Tanner stages II–IV) or who had reached full puberty (stage V) were considered to be undergoing puberty or pubertal. Blood pressure was measured in the right arm by the auscultatory procedure using a standard mercury sphygmomanometer. A cuff adequate for the size of the upper arm of the child was used. Systolic and diastolic blood pressure was measured three times after a 10-min rest in the supine position.Biochemical variablesA blood sample was drawn from the antecubital vein, after fasting for at least 10h, to measure blood glucose, uric acid, and lipids (total cholesterol, triglycerides, and HDL-C). Tests were performed using enzymatic methods with a Hitachi 911® autoanalyzer and Cienvar reagents. LDL-C was estimated using the Friedewald equation, where LDL-C=total cholesterol−(HDL-C+[triglycerides/5]). Non-HDL cholesterol (non-HDL-C) was estimated as total cholesterol−HDL-C. The triglyceride/HDL-C (Tg/HDL-C), total cholesterol/HDL-C (TC/HDL-C), and LDL-C/HDL-C ratios were calculated. A serum aliquot was stored at −20°C, and fasting insulin levels were subsequently measured by immunoassay (ELISA) using commercial kits from DRG Instruments GmbH, Germany, with intra-assay and inter-assay coefficients of variation ranging from 1.8% to 2.6% and from 2.9% to 6% respectively. Tests were performed at the hormone laboratory of IAHULA. Under conditions of strict quality control. These data were used to assess insulin resistance using the Homeostasis Model Assessment (HOMA) formula: HOMA-IR=fasting insulin (μIU/mL)×fasting glucose (mmol/L)/22.5. High basal insulin values were defined as those higher than 12μU/mL, and high HOMA-IR values as those higher than 2.5. Both values are >P95 of a representative sample of children and adolescents from the city of Mérida (CREDEFAR study).<a class="elsevierStyleCrossRef" href="#bib0235">18</a>Echocardiographic measurement of epicardial adipose tissueA two-dimensional (2D) transthoracic echocardiogram using a standard procedure was performed, with the patient in the left lateral decubitus position. EAT thickness was measured by a pediatric echocardiographer using the procedure validated by Iacobellis et al.<a class="elsevierStyleCrossRef" href="#bib0240">19</a>EAT was identified as the echolucent space between the external wall of the myocardium and the visceral layer of the pericardium. This thickness was measured perpendicularly on the free wall of the right ventricle at the end of systole in three cardiac cycles, using a parasternal long or parasternal short axis view. Measurement was taken on the free wall of the right ventricle for two reasons: (1) this point is anatomically recognized as the one with the greatest epicardial fat thickness, and (2) the parasternal long and parasternal short axes allow for more accurate measures of EAT on the right ventricle, with an optimum slide orientation in each view.<a class="elsevierStyleCrossRefs" href="#bib0245">20,21</a>Statistical analysisContinuous variables are given as mean±standard deviation, and categorical variables as numbers and percentages. A Chi-square test was used to assess potential sex-related differences between the groups and to establish associations between the categorical variables. In order to determine the difference in the means of the continuous variables between subjects with less and more than two CRFs, a Student's t test for independent data was used for normally distributed variables, and a Mann–Whitney U test was used for non-normally distributed variables (glucose, total cholesterol, LDL-C, non-HDL-C, insulin, and HOMA-IR). A receiver operating curve (ROC) was constructed to determine the cut-off point of EAT thickness for predicting the presence of two or more CRFs; for this, an area under the curve (AUC) of 1.00 was considered as optimum, an AUC ranging from 0.90 to 0.97 as very good, an AUC from 0.75 to 0.90 as good, and an AUC from 0.60 to 0.75 as fair. AUCs under 0.60 were considered to be a poorly valid test. To estimate the optimum cut-off point from ROC, the Youden index was calculated using the formula: (J=sensitivity+specificity−1=S−[1−Sp]). A Pearson's correlation matrix was performed between the quantitative variables. A linear regression analysis was also performed, with EAT as the dependent variable, to determine which variable had greater statistical significance, as well as a logistic regression analysis with or without two or more CRFs as the dependent variable and EAT thickness and BMI as the independent variables, in order to determine which of them had greater statistical significance for the presence of CRFs. SPSS version 19.0 for Windows was used for statistical analysis, and a value of p<0.05 was considered statistically significant.ResultsSeventy-seven children and adolescents were enrolled into the study. The group with less than two CRFs consisted of 40 subjects, 45% girls and 55% boys, with a mean age of 12.30±3.14 years; 32.5% were 6–9 years old, 32.5% were 10–13 years old, and 35% were 14–18 years old. Forty-five percent of the subjects were prepubertal (Tanner stage I), 35% were undergoing puberty (Tanner stages II–IV), and 20% were pubertal (Tanner stage V). The mean BMI was 22.19±3.95kg/m2, and the BMI Z-score was 0.9±1.15. The group with less than two or more CRFs consisted of 37 subjects, 51.4% girls and 48.6% boys, with a mean age of 11.60±3.16 years; 40.5% were 6–9 years old, 37.8% were 10–13 years old, and 21.6% were 14–18 years old; 56.8% of these subjects were prepubertal, 24.3% were undergoing puberty, and 18.9% were pubertal; the mean BMI was 25.39±5.00kg/m2, and the BMI Z-score was 1.59±0.86. There were no statistically significant differences between the groups in distribution by sex, age, pubertal stage, family history of CRFs, weight, or height. The BMI, AC, SBP, and DBP were significantly higher in the group with more than two CRFs (p<0.05 for SBP and p<0.009 for all other variables). There were 23 (29.9%) participants with normal weight, 21 (27.3%) with overweight, and 33 (42.9%) with obesity, and a significantly greater frequency of participants with obesity was found in the group with two or more CRFs (p<0.05) (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>An analysis of the biochemical variables showed that the group of subjects with two or more CRFs had significantly higher values of blood glucose, triglycerides (p<0.05), total cholesterol, and LDL-C, as well as Tg/HDL-C, TC/HDL-C, and LDL-C/HDL-C ratios (p<0.005), than the group with less than two CRFs, while plasma HDL-C levels were significantly lower in the group of children and adolescents with two or more CRFs (p<0.05) (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>). The most common risk factor was abdominal obesity (50.6%), followed by hypercholesterolemia (27.3%), high blood pressure (24.7%), decreased HDL-C (24.7%), and hypertriglyceridemia (22.1%). The least common risk factor was hyperglycemia (13%).<elsevierMultimedia ident="tbl0010"></elsevierMultimedia><a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> shows that the group of subjects with two or more CRFs had greater EAT thickness (3.13 vs 2.76mm), basal insulin (16.56 vs 10.92μU/mL), and HOMA-IR (4.06 vs 2.30) values as compared to participants with less than two CRFs (p<0.05). Higher values of EAT (p<0.001), insulin, and HOMA-IR (p<0.001 and p<0.05) were also seen in the group with obesity, abdominal obesity, and HBP-preHBP. HOMA-IR values were higher in participants with fasting hyperglycemia (p<0.05).<elsevierMultimedia ident="tbl0015"></elsevierMultimedia>The ROC for the group of children and adolescents categorized based on the presence of CRFs had an AUC of 0.64 (95% CI: 0.52–0.77), which rates the test as fair. The cut-off point of EAT thickness as a predictor of two or more CRFs was 3.17mm (J=0.267), with a 55.6% sensitivity and a 71.1% specificity (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>A). The indirect relative risk or odds ratio of an individual having two or more risk factors if he/she had an elevated EAT thickness, taking as reference the cut-off point of 3.17mm obtained in the ROC analysis, was 3.1-fold greater than that of subjects with a lower value (95% CI: 1.174–8.022; p=0.020).<elsevierMultimedia ident="fig0005"></elsevierMultimedia>A correlation analysis found that EAT, measured in millimeters, had a highly significant positive correlation to the BMI (r=0.561; p=0.0001), SBP (r=0.256; p=0.028), plasma insulin levels (r=0.408; p=0.0001), and HOMA-IR (r=0.325; p=0.005) (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>). EAT also positively correlated to AC (r=0.549; p=0.0001). No correlation was found between EAT and lipid variables. On the other hand, a very significant correlation was seen between the BMI and SBP (r=0.423; p=0.0001), insulin (r=0.460; p=0.0001), and HOMA-IR (r=0.418; p=0.0001) (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>). Adjusted or controlled partial correlations were performed for the BMI, and significant correlations of EAT with abdominal circumference, SBP, insulin, and HOMA-IR were seen to lose their significance.<elsevierMultimedia ident="fig0010"></elsevierMultimedia><elsevierMultimedia ident="fig0015"></elsevierMultimedia>In the simple linear regression analysis with EAT thickness as the dependent variable, SBP, insulin, HOMA-IR, AC, and the BMI were significant. In the multiple linear regression analysis, however, SBP, insulin, HOMA-IR, and AC lost statistical significance, while BMI significance persisted (p=0.041), being the variable which had the greatest impact on EAT thickness, with an R-squared of 0.352, which meant that the BMI accounted for 35% of EAT (<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>).<elsevierMultimedia ident="tbl0020"></elsevierMultimedia>A logistic regression analysis with or without two or more CRFs as the dependent variable and EAT thickness and BMI as independent variables was performed to determine which of them had greater statistical significance for the presence of CRFs. It was found that in the univariate analysis, both EAT and BMI were significant. In the multivariate analysis, however, EAT lost significance, and it was therefore established that the BMI had a greater influence, with an R2 of 0.175 and an indirect relative risk or odds ratio of 1.20 (95% CI: 1.028–1.406) (<a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>).<elsevierMultimedia ident="tbl0025"></elsevierMultimedia>DiscussionThe main findings of this study include: (1) children and adolescents with two or more CRFs have greater EAT thickness as compared to the group with less than two CRFs; (2) the cut-off point of EAT thickness that makes it possible to predict the presence of two or more CRFs is 3.17mm; (3) a positive correlation exists between EAT thickness and other anthropometric (BMI, AC), clinical (SBP), and biochemical (insulin and HOMA-IR) variables, which is lost after the adjustment of correlation for the BMI; (4) the BMI was the variable with the greatest impact on EAT thickness and the occurrence of two or more CRFs.No prior studies are available in Venezuela assessing EAT thickness in children and adolescents, but in Latin America Cabrera-Rego et al.<a class="elsevierStyleCrossRef" href="#bib0255">22</a> showed greater EAT thickness (2.76±1.2 vs 1.36±0.7mm, p=0.001) in obese children and adolescents as compared to a control group. These results agree with those of our study, which showed that subjects with two or more CRFs had greater EAT values than those with less than 2 CRFs (3.13 vs 2.76mm), and that obese children and adolescents had values significantly higher than non-obese subjects (3.43 vs 2.61mm).To the best our knowledge, there have been no previous studies proposing cut-off points of EAT for predicting the presence of CRFs in a Latin American pediatric population. In a European population, Abaci et al.<a class="elsevierStyleCrossRef" href="#bib0260">23</a> showed that EAT thickness greater than 4.1mm had a 90% sensitivity and a 61% specificity for predicting insulin resistance in children with obesity. Cena et al.<a class="elsevierStyleCrossRef" href="#bib0210">13</a> recently reported that, in a population of 102 Italian male adolescents, the optimum cut-off point of EAT thickness predicting for visceral obesity was 3.2mm. This value is similar to the cut-off point of EAT found in our study as a predictor of the presence of two or more CRFs (3.17mm). These small differences were previously reported in an adult population, and may be due to ethnic differences in body fat distribution.<a class="elsevierStyleCrossRef" href="#bib0190">9</a>Our results agree with those reported in other studies showing that EAT, measured by echocardiography, is related from childhood to the anthropometric, clinical, and biochemical components of MS.<a class="elsevierStyleCrossRefs" href="#bib0200">11,12,24</a> Insulin resistance is considered the core of MS. In this regard, a two-fold greater release rate of fatty acids by epicardial adipocytes as compared to perirenal fat has been reported in animal models. This suggests high lipolytic activity that is probably due to the reduced antilipolytic effect of insulin in this tissue and an increased expression of β-adrenergic receptors, especially β-3 receptors, whose stimulation activates lipolysis and increases the release of free fatty acids able to promote blood pressure increase through different pathways, including adrenergic stimulation, increased oxidative stress, endothelial dysfunction, and vascular cell growth.<a class="elsevierStyleCrossRefs" href="#bib0270">25,26</a> These observations explain the correlation between EAT and SBP, and suggest that epicardial fat is a tissue with high insulin resistance. This is supported by the fact that, as in prior studies, a significant correlation was seen between EAT thickness, basal plasma insulin concentration, and HOMA-IR. In addition, Manco et al.<a class="elsevierStyleCrossRef" href="#bib0280">27</a> showed in obese prepubertal and pubertal children that at an early age, EAT is a significant marker of increased insulin resistance.The multiple linear regression analysis showed that the BMI was the variable that most influenced EAT thickness. This results confirms that obesity is a factor predisposing to epicardial fat increase.<a class="elsevierStyleCrossRefs" href="#bib0170">5,28</a> As a novel contribution in this regard, recent research has proposed EAT as a therapeutic target for different interventions in obese patients.<a class="elsevierStyleCrossRefs" href="#bib0210">13,29</a> It should be emphasized that while AC is universally considered to be the most accessible visceral fat marker, in this study the BMI had a greater influence on EAT thickness. It has also been shown that the BMI was the variable with the greatest impact on CRF occurrence. These findings agree with those reported by Schusterova et al.<a class="elsevierStyleCrossRef" href="#bib0265">24</a> in children and adolescents with overweight and obesity. These authors showed that the coefficients of correlation of EAT with various CRFs are similar to or better than those of AC, but are not greater than those seen with the BMI. This suggests that EAT thickness measured by echocardiography is not a stronger indicator of cardiometabolic risk in childhood than the BMI.In conclusion, in this group of children and adolescents, the relationship of EAT to CRFs was found to be dependent on the BMI, and the BMI was established as the dependent variable which most influenced EAT thickness.FundingThis study was conducted in part thanks to funding received from the Council of Scientific, Humanistic, Technological, and Art Development of Universidad de Los Andes (CDCHTA-ULA) under projects M-1013-11-07-AA and ADG M-10, and also from the National Fund for Science, Technology and Innovation (FONACIT) of the Ministry of Popular Power for Science, Technology and Innovation under project no. 2012000970." "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres618599" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "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" => "xpalclavsec632623" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres618600" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec632622" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Materials and methods" "secciones" => array:1 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Subjects" ] ] ] 6 => array:3 [ "identificador" => "sec0020" "titulo" => "Procedure" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0025" "titulo" => "Clinical evaluation" ] 1 => array:2 [ "identificador" => "sec0030" "titulo" => "Biochemical variables" ] 2 => array:2 [ "identificador" => "sec0035" "titulo" => "Echocardiographic measurement of epicardial adipose tissue" ] ] ] 7 => array:2 [ "identificador" => "sec0040" "titulo" => "Statistical analysis" ] 8 => array:2 [ "identificador" => "sec0045" "titulo" => "Results" ] 9 => array:2 [ "identificador" => "sec0050" "titulo" => "Discussion" ] 10 => array:2 [ "identificador" => "sec0055" "titulo" => "Funding" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2015-06-15" "fechaAceptado" => "2015-09-08" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec632623" "palabras" => array:4 [ 0 => "Epicardial adipose tissue" 1 => "Epicardial fat" 2 => "Cardiometabolic risk factors" 3 => "Children and adolescents" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec632622" "palabras" => array:4 [ 0 => "Tejido adiposo epicárdico" 1 => "Grasa epicárdica" 2 => "Factores de riesgo cardiometabólico" 3 => "Niños y adolescentes" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "ObjectiveTo assess the relationship of epicardial adipose tissue (EAT) thickness with cardiometabolic risk factors (CRFs) in children and adolescents. MethodsSeventy-seven subjects of both sexes aged 7–18 years were selected. Medical history, clinical parameters, and glucose, insulin, and lipid levels were collected. EAT thickness was measured using transthoracic echocardiography. Study subjects were divided into two groups based on whether they had less than two or two or more CRFs. ResultsThe group with two or more CRFs had higher EAT thickness, insulin, and HOMA-IR values (p<0.05). EAT thickness showed a statistically significant positive correlation with body mass index (BMI) (r=0.561, p=0.0001), waist circumference (r=0.549, p=0.0001), systolic blood pressure (SBP) (r=0.256, p=0.028), insulin (r=0.408, p=0.0001), and HOMA-IR (r=0.325, p=0.005). However, these correlations were not significant after adjustment for BMI. The cut-off point for EAT thickness as predictor of two or more CRFs was 3.17mm. The risk (odds ratio) of having two or more CRFs if EAT thickness was >3.17mm was 3.1 (95% CI: 1.174–8.022). BMI was the independent variable that most affected EAT thickness and the presence of two or more CRFs. ConclusionIn this group of children and adolescents, the relationship of EAT thickness with CRFs was found to be dependent on BMI." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "ObjetivoDeterminar la relación del espesor del tejido adiposo epicárdico (TAE) con factores de riesgo cardiometabólico (FRC) en niños y adolescentes. MétodosSe seleccionaron 77 sujetos de ambos sexos entre 7 y 18 años. Se realizó anamnesis y evaluación de parámetros clínicos, determinación de glucemia, insulina y lípidos y se calculó el HOMA-IR. Se determinó el espesor del TAE mediante ecocardiografía transtorácica. Se formaron 2 grupos, participantes con menos de 2 FRC (cero o un FRC) y participantes con 2 o más FRC. ResultadosEl grupo con 2 o más FRC presentó mayores valores de espesor del TAE, insulina y HOMA-IR (p<0,05). El espesor del TAE mostró una correlación positiva estadísticamente muy significativa con el índice de masa corporal (IMC) (r=0,561; p=0,0001), la circunferencia abdominal (r=0,549; p=0,0001), la presión arterial sistólica (PAS) (r=0,256; p=0,028), la insulina (r=0,408; p=0,0001) y el HOMA-IR (r=0,325; p=0,005), sin embargo, estas correlaciones fueron no significativas al ajustar para el IMC. El punto de corte para el espesor del TAE como predictor de 2 o más FRC fue de 3,17mm. El riesgo (odds ratio) de tener 2 o más FRC si presenta un espesor de TAE>3,17mm fue de 3,1 (IC: 1,174–8,022, p=0,02). El IMC fue la variable independiente que más influyó sobre los valores del espesor del TAE y la presencia de 2 o más FRC. ConclusiónEn este grupo de niños y adolescentes se encontró que la relación del TAE con los FRC es dependiente del IMC." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "Please cite this article as: Reyes Y, Paoli M, Camacho N, Molina Y, Santiago J, Lima-Martínez MM. Espesor del tejido adiposo epicárdico en niños y adolescentes con factores de riesgo cardiometabólico. Endocrinol Nutr. 2016;63:70–78." ] ] "multimedia" => array:8 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1048 "Ancho" => 2601 "Tamanyo" => 140633 ] ] "descripcion" => array:1 [ "en" => "ROC for establishing the cut-off point of EAT thickness for predicting two or more CRFs in this sample of children and adolescents." ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 2075 "Ancho" => 2643 "Tamanyo" => 204194 ] ] "descripcion" => array:1 [ "en" => "Correlations of EAT with the BMI, SBP, insulin, and HOMA-IR in the study subjects." ] ] 2 => array:7 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 2218 "Ancho" => 1590 "Tamanyo" => 176774 ] ] "descripcion" => array:1 [ "en" => "Correlations of the BMI with SBP, insulin, and HOMA-IR in the study subjects." ] ] 3 => array:7 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:3 [ "leyenda" => "Data are means±SD or No. (%).BMI, body mass index; DBP, diastolic blood pressure; SBP, systolic blood pressure." "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">Variables \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=77) \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">Less than 2 CRFs (n=40) \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">Two or more CRFs (n=37) \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">Sex F/M \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">37 (48.1)/40(51.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">18 (45.0)/22 (55.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">19 (51.4)/18 (48.6) \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">Age (years) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">11.96±3.15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">12.30±3.14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">11.60±3.16 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top">Age groups – No. (%)</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">6–9 years \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">28 (36.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">13 (32.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">15 (40.5) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">10–13 years \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">27 (35.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">13 (32.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">14 (37.8) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">14–18 years \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">22 (28.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">14 (35.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">8 (21.6) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top">Pubertal stage</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Prepubertal \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">39 (50.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">18 (45.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">21 (56.8) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Undergoing puberty \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">23 (29.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">14 (35.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">9 (24.3) \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">Pubertal \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">15 (19.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">8 (20.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7 (18.9) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Family hist. CRFs – No. (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">73 (94.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">37 (92.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">36 (97.3) \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">Weight (kg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">51.10±14.84 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">48.02±14.19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">54.43±14.99 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Height (kg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">146.66±12.80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">146.76±14.43 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">146.54±10.96 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">BMI (kg/m2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">23.73±4.74 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">22.19±3.95 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">25.39±5.00<a class="elsevierStyleCrossRef" href="#tblfn0010">**</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">BMI Z-score \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.23±1.07 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.90±1.15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.59±0.86<a class="elsevierStyleCrossRef" href="#tblfn0010">**</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Normal weight \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">23(29.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">15 (37.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">8 (21.6) \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">Overweight \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">21 (27.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">13 (32.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">8 (21.6) \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">Obesity \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">33 (42.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">12 (30) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">21 (56.8)<a class="elsevierStyleCrossRef" href="#tblfn0005">*</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Waist (cm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">77.64±11.20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">74.05±9.89 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">81.53±11.35<a class="elsevierStyleCrossRef" href="#tblfn0010">**</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">SBP (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">107.31±9.83 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">104.55±9.69 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">110.29±9.20<a class="elsevierStyleCrossRef" href="#tblfn0010">**</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">DBP (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">65.70±7.05 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">63.94±7.08 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">67.60±6.59<a class="elsevierStyleCrossRef" href="#tblfn0005">*</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1012693.png" ] ] ] "notaPie" => array:2 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "*" "nota" => "p<0.05." ] 1 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "**" "nota" => "p<0.009." ] ] ] "descripcion" => array:1 [ "en" => "Demographic and clinical data of patients categorized based on the presence of cardiometabolic risk factors (CRFs)." ] ] 4 => array:7 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:3 [ "leyenda" => "Data are means±SD." "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">Variables \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">Less than 2 CRFs (n=40) \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">Two or more CRFs (n=37) \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">Blood glucose (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">83.47±9.29 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">103.18±41.12<a class="elsevierStyleCrossRef" href="#tblfn0015">*</a> \t\t\t\t\t\t\n \t\t\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="char" valign="top">71.42±43.30 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">93.48±48.09<a class="elsevierStyleCrossRef" href="#tblfn0015">*</a> \t\t\t\t\t\t\n \t\t\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="char" valign="top">144.37±31.64 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">201.43±83.44<a class="elsevierStyleCrossRef" href="#tblfn0020">**</a> \t\t\t\t\t\t\n \t\t\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-C (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">87.62±30.32 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">144.27±74.65<a class="elsevierStyleCrossRef" href="#tblfn0020">**</a> \t\t\t\t\t\t\n \t\t\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-C (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42.22±5.14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">38.43±7.34<a class="elsevierStyleCrossRef" href="#tblfn0015">*</a> \t\t\t\t\t\t\n \t\t\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-HDL-C (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">102.15±32.82 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">163.00±81.20<a class="elsevierStyleCrossRef" href="#tblfn0020">**</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Tg/HDL-C \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.73±1.14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.49±1.34<a class="elsevierStyleCrossRef" href="#tblfn0020">**</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">TC/HDL-C \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.48±0.90 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.28±1.99<a class="elsevierStyleCrossRef" href="#tblfn0020">**</a> \t\t\t\t\t\t\n \t\t\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-C/HDL-C \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.13±0.80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.78±1.82<a class="elsevierStyleCrossRef" href="#tblfn0020">**</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1012697.png" ] ] ] "notaPie" => array:2 [ 0 => array:3 [ "identificador" => "tblfn0015" "etiqueta" => "*" "nota" => "p<0.05." ] 1 => array:3 [ "identificador" => "tblfn0020" "etiqueta" => "**" "nota" => "p<0.005." ] ] ] "descripcion" => array:1 [ "en" => "Biochemical variables of subjects categorized based on the presence of cardiometabolic risk factors (CRFs)." ] ] 5 => array:7 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:3 [ "leyenda" => "Data are means±SD." "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">Variables \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">Less than 2 CRFs (n=40) \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">Two or more CRFs (n=37) \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">EAT (mm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.76±0.78 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.13±0.73<a class="elsevierStyleCrossRef" href="#tblfn0025">*</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Insulin (μU/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">10.92±10.17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">16.56±11.57<a class="elsevierStyleCrossRef" href="#tblfn0030">**</a> \t\t\t\t\t\t\n \t\t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.30±2.38 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4.06±2.79<a class="elsevierStyleCrossRef" href="#tblfn0030">**</a> \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"></td></tr><tr title="table-row"><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">No obesity (n=44) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Obesity (n=33) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">EAT (mm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.61±0.65 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.43±0.70<a class="elsevierStyleCrossRef" href="#tblfn0030">**</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Insulin (μU/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">10.05±9.17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">18.49±11.92<a class="elsevierStyleCrossRef" href="#tblfn0030">**</a> \t\t\t\t\t\t\n \t\t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.34±2.17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4.24±3.04<a class="elsevierStyleCrossRef" href="#tblfn0030">**</a> \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"></td></tr><tr title="table-row"><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">No abdominal ob. (n=38) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Abdominal ob. (n=39) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">EAT (mm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.58±0.59) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.32±0.78<a class="elsevierStyleCrossRef" href="#tblfn0030">**</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Insulin (μU/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">8.58±5.25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">18.59±13.15<a class="elsevierStyleCrossRef" href="#tblfn0030">**</a> \t\t\t\t\t\t\n \t\t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.07±1.57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4.20±3.19<a class="elsevierStyleCrossRef" href="#tblfn0030">**</a> \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"></td></tr><tr title="table-row"><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">No HBP (n=58) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">HBP-preHBP (n=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">EAT (mm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.78±0.73 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.45±0.70<a class="elsevierStyleCrossRef" href="#tblfn0030">**</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Insulin (μU/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">12.48±11.56 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">17.04±9.21<a class="elsevierStyleCrossRef" href="#tblfn0025">*</a> \t\t\t\t\t\t\n \t\t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.81±2.70 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4.14±2.59<a class="elsevierStyleCrossRef" href="#tblfn0025">*</a> \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"></td></tr><tr title="table-row"><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Normal blood glucose (n=67) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">High blood glucose (n=10) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">EAT (mm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.98±0.80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.68±0.57 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Insulin (μU/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">13.56±11.39 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">13.78±9.83 \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">HOMA-IR \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.84±2.57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">5.23±2.97<a class="elsevierStyleCrossRef" href="#tblfn0025">*</a> \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"></td></tr><tr title="table-row"><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">No dyslipidemia (n=35) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Dyslipidemia (n=42) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">EAT (mm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.01±0.87 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.88±0.69 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Insulin (μU/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">13.72±11.58 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">13.48±10.92 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">HOMA-IR \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.94±2.70 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.30±2.76 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1012694.png" ] ] ] "notaPie" => array:2 [ 0 => array:3 [ "identificador" => "tblfn0025" "etiqueta" => "*" "nota" => "p<0.05." ] 1 => array:3 [ "identificador" => "tblfn0030" "etiqueta" => "**" "nota" => "p<0.001." ] ] ] "descripcion" => array:1 [ "en" => "Epicardial adipose tissue (EAT), basal insulin, and HOMA-IR values in patients categorized based on the presence of cardiovascular risk factors (CRFs)." ] ] 6 => array:7 [ "identificador" => "tbl0020" "etiqueta" => "Table 4" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:1 [ "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">Independent variables \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">Simple \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">Multiple \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="" valign="top" scope="col"> \t\t\t\t\t\t\n \t\t\t\t</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">p value \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 value \t\t\t\t\t\t\n \t\t\t\t</th><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></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">SBP (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.028 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.877 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" 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">Insulin (μU/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.0001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.154 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" 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">HOMA-IR \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.005 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.345 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" 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">Waist \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.0001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.527 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" 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">BMI (kg/m2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.0001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.041 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">R2: 0.352 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">B coeff.: 0.060 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CI: 0.002–0.118 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1012696.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Simple and multiple linear regression analysis of variables related to EAT thickness as the dependent variable." ] ] 7 => array:7 [ "identificador" => "tbl0025" "etiqueta" => "Table 5" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:1 [ "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 " align="left" valign="top" scope="col">Univariate \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">Multivariate \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="" valign="top" scope="col"> \t\t\t\t\t\t\n \t\t\t\t</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">p value \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 value \t\t\t\t\t\t\n \t\t\t\t</th><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></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">Epicardial adipose tissue (mm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.049 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.779 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">R2: 0.175 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Body mass index (kg/m2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.007 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.021 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Odds ratio: 1.20 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CI: 1.028–1.406 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1012695.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Logistic regression analysis with or without two CRFs as the dependent variable and EAT thickness and body mass index as independent variables." ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:29 [ 0 => array:3 [ "identificador" => "bib0150" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Cardiometabolic risk variables in overweight and obese children: a worldwide comparison" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "M. 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Epicardial adipose tissue thickness in children and adolescents with cardiometabolic risk factors

Espesor del tejido adiposo epicárdico en niños y adolescentes con factores de riesgo cardiometabólico

Yubriangel Reyesa, Mariela Paolia,

Corresponding author

paolimariela@hotmail.com

Corresponding author.

, Nolis Camachob, Yudisay Molinac, Justo Santiagoc, Marcos M. Lima-Martínezd

a Unidad de Endocrinología, Instituto Autónomo Hospital Universitario de los Andes, Mérida, Venezuela

b Unidad de Nutrición, Crecimiento y Desarrollo Infantil, Instituto Autónomo Hospital Universitario de los Andes, Mérida, Venezuela

c Instituto de Investigaciones Cardiovasculares, Instituto Autónomo Hospital Universitario de los Andes, Mérida, Venezuela

d Departamento de Ciencias Fisiológicas, Universidad de Oriente, Núcleo Bolívar, Ciudad Bolívar, Venezuela

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    "titulo" => "Epicardial adipose tissue thickness in children and adolescents with cardiometabolic risk factors"
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          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">ROC for establishing the cut-off point of EAT thickness for predicting two or more CRFs in this sample of children and adolescents&#46;</p>"
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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Different studies have shown that obesity&#44; together with other cardiometabolic risk factors &#40;CRFs&#41;&#44; is associated with subclinical markers of atherosclerosis in children and adolescents&#44;<a class="elsevierStyleCrossRefs" href="#bib0150"><span class="elsevierStyleSup">1&#44;2</span></a> and with early mortality in adulthood&#46;<a class="elsevierStyleCrossRefs" href="#bib0160"><span class="elsevierStyleSup">3&#44;4</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Interest in organ-specific adiposity has increased rapidly in recent years&#46; In this context&#44; epicardial adipose tissue &#40;EAT&#41;&#44; the visceral fat of the heart&#44; has emerged as a new cardiometabolic risk marker because of its close anatomical proximity to the myocardium and coronary artery&#44; its endocrine and metabolic properties&#44; and its diagnostic and therapeutic value&#46;<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">5</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">EAT thickness is consistently associated with metabolic syndrome &#40;MS&#41; and its components&#44;<a class="elsevierStyleCrossRefs" href="#bib0175"><span class="elsevierStyleSup">6&#44;7</span></a> but changes markedly with age and between subjects from different ethnic groups&#44; which has prevented agreement on a single general cut-off point for predicting the risk of MS&#46;<a class="elsevierStyleCrossRefs" href="#bib0185"><span class="elsevierStyleSup">8&#44;9</span></a> In Venezuela EAT thickness greater than 5<span class="elsevierStyleHsp" style=""></span>mm was shown to have a good sensitivity and specificity for predicting MS<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">10</span></a>&#59; that study&#44; however&#44; was conducted in an adult population&#44; and its results are therefore not applicable to children and adolescents&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">A significant correlation has been shown in obese children between EAT thickness and other anthropometric variables such as the body mass index &#40;BMI&#41; and abdominal circumference &#40;AC&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">11</span></a> Kim et al&#46;<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">12</span></a> similarly showed that EAT thickness measured by echocardiography is a practical and accurate marker of visceral obesity in adolescents&#46; In fact&#44; sedentary adolescents have been shown to have greater EAT thickness as compared to non-sedentary ones&#44; and each 1-mm increase in EAT thickness increases sevenfold the risk of visceral obesity&#46;<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">13</span></a></p><p id="par0025" class="elsevierStylePara elsevierViewall">Recently&#44; a 2&#46;2&#37; prevalence of MS has been reported in children and adolescents from M&#233;rida&#44; Venezuela&#59; however&#44; this population has a high frequency of abdominal obesity&#44; hypertriglyceridemia&#44; and high blood pressure&#46;<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">14</span></a> No prior studies assessing EAT thickness in our children and adolescents are available&#46; This study was therefore undertaken to assess EAT thickness in children and adolescents with CRFs&#44; to ascertain to what extent our results were consistent with the few data available&#44; and thus to make better use of the currently available diagnostic tools&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Materials and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Subjects</span><p id="par0030" class="elsevierStylePara elsevierViewall">This was an observational&#44; cross-sectional&#44; analytical study&#46; Participating subjects were selected from the outpatient clinics of endocrinology&#44; nutrition&#44; growth and pediatric development of the Instituto Aut&#243;nomo Hospital Universitario de los Andes and the general population of M&#233;rida&#44; Venezuela&#46; When sample size was considered&#44; no studies were found comparing EAT thickness between children and adolescents&#44; and estimation was therefore based on obese and non-obese data&#46; Specifically&#44; EAT thickness data from Mazur et al&#46;<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">11</span></a> were used&#58; 2&#46;5<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;81<span class="elsevierStyleHsp" style=""></span>mm for non-obese children and 5&#46;5<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>1&#46;98<span class="elsevierStyleHsp" style=""></span>mm for obese children&#44; with an <span class="elsevierStyleItalic">&#945;</span> error of 0&#46;05 and a <span class="elsevierStyleItalic">&#946;</span> error of 0&#46;20&#46; The final sample size was 30 subjects per group&#46; Overweight and obese subjects are known to have a greater frequency of CRFs than subjects with normal weight&#46; Thus&#44; overweight and obese individuals of both sexes aged 6&#8211;18 years of age were initially enrolled sequentially&#44; and age- and sex-matched subjects with normal weight were subsequently selected to obtain comparable groups&#44; which only differed in the number of CRFs&#46; The participants came from different clinics and from the general population&#46; Subjects with primary hyperlipidemia and endocrine diseases such as diabetes mellitus&#44; hypothyroidism&#44; and Cushing&#39;s syndrome&#44; as well as any comorbidity or intake of drugs &#40;glucocorticoids&#44; lipid-lowering&#44; antiepileptic&#41; that could affect the tested variables were excluded from the study&#46;</p><p id="par0035" class="elsevierStylePara elsevierViewall">The subjects were split into two groups based on the presence of CRFs&#58; a control group consisting of subjects with less than two CRFs &#40;no or one CRF&#41; and a study group consisting of subjects with two or more CRFs&#46; The CRFs considered included basal blood glucose<span class="elsevierStyleHsp" style=""></span>&#8805;<span class="elsevierStyleHsp" style=""></span>100<span class="elsevierStyleHsp" style=""></span>mg&#47;dL &#40;fasting hyperglycemia&#41;&#59; AC<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>P90 &#40;respective age and sex-abdominal obesity&#41;&#59; systolic &#40;SBP&#41; and&#47;or diastolic blood pressure &#40;DBP&#41;<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>P90 &#40;respective age and sex-preHBP and HBP&#41;&#59; triglycerides<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>P90 &#40;respective age and sex-hypertriglyceridemia&#41;&#59; HDL-C<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>P10 &#40;respective age and sex-low HDL-C&#41;&#59; and LDL-C<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>P90 &#40;respective age and sex-hypercholesterolemia&#41;&#46; The percentile distribution of the local population obtained in the CREDEFAR study was used as a reference&#46;<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">14&#44;15</span></a> In compliance with ethical guidelines in the Declaration of Helsinki&#44; only children and adolescents whose legal representative agreed to participation and signed the informed consent were enrolled into the study&#46;</p></span></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Procedure</span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Clinical evaluation</span><p id="par0040" class="elsevierStylePara elsevierViewall">Weight and height were measured under fasting conditions and with subjects in their underwear&#46; The body mass index &#40;BMI&#41; was calculated as weight divided by squared height&#46; Obesity was defined as a BMI<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>P97 for age and sex in the curves for Venezuelan children and adolescents prepared by FUNDACREDESA&#44;<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">16</span></a> overweight as BMI values &#62;P90 and &#8804;P97&#44; normal weight as a BMI ranging from P10 to P90&#44; and low weight as BMI<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>P10&#46; The <span class="elsevierStyleItalic">Z</span>-score of the BMI was determined&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">17</span></a> Abdominal circumference &#40;AC&#41; was measured in centimeters at the end of an expiration&#44; with the subjects standing&#44; at the level of the midline between the lower margin of the last rib and the iliac crest&#46; Pubertal development was determined based on the Tanner stage in breast and pubic hair in girls&#44; and in genitalia and pubic hair in boys&#46; Subjects were considered prepubertal if they had no secondary sexual characteristics &#40;Tanner I&#41;&#44; while those with some secondary characteristics &#40;Tanner stages II&#8211;IV&#41; or who had reached full puberty &#40;stage V&#41; were considered to be undergoing puberty or pubertal&#46; Blood pressure was measured in the right arm by the auscultatory procedure using a standard mercury sphygmomanometer&#46; A cuff adequate for the size of the upper arm of the child was used&#46; Systolic and diastolic blood pressure was measured three times after a 10-min rest in the supine position&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Biochemical variables</span><p id="par0045" class="elsevierStylePara elsevierViewall">A blood sample was drawn from the antecubital vein&#44; after fasting for at least 10<span class="elsevierStyleHsp" style=""></span>h&#44; to measure blood glucose&#44; uric acid&#44; and lipids &#40;total cholesterol&#44; triglycerides&#44; and HDL-C&#41;&#46; Tests were performed using enzymatic methods with a Hitachi 911<span class="elsevierStyleSup">&#174;</span> autoanalyzer and Cienvar reagents&#46; LDL-C was estimated using the Friedewald equation&#44; where LDL-C<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>total cholesterol<span class="elsevierStyleHsp" style=""></span>&#8722;<span class="elsevierStyleHsp" style=""></span>&#40;HDL-C<span class="elsevierStyleHsp" style=""></span>&#43;<span class="elsevierStyleHsp" style=""></span>&#91;triglycerides&#47;5&#93;&#41;&#46; Non-HDL cholesterol &#40;non-HDL-C&#41; was estimated as total cholesterol<span class="elsevierStyleHsp" style=""></span>&#8722;<span class="elsevierStyleHsp" style=""></span>HDL-C&#46; The triglyceride&#47;HDL-C &#40;Tg&#47;HDL-C&#41;&#44; total cholesterol&#47;HDL-C &#40;TC&#47;HDL-C&#41;&#44; and LDL-C&#47;HDL-C ratios were calculated&#46; A serum aliquot was stored at &#8722;20<span class="elsevierStyleHsp" style=""></span>&#176;C&#44; and fasting insulin levels were subsequently measured by immunoassay &#40;ELISA&#41; using commercial kits from DRG Instruments GmbH&#44; Germany&#44; with intra-assay and inter-assay coefficients of variation ranging from 1&#46;8&#37; to 2&#46;6&#37; and from 2&#46;9&#37; to 6&#37; respectively&#46; Tests were performed at the hormone laboratory of IAHULA&#46; Under conditions of strict quality control&#46; These data were used to assess insulin resistance using the Homeostasis Model Assessment &#40;HOMA&#41; formula&#58; HOMA-IR<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>fasting insulin &#40;&#956;IU&#47;mL&#41;<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>fasting glucose &#40;mmol&#47;L&#41;&#47;22&#46;5&#46; High basal insulin values were defined as those higher than 12<span class="elsevierStyleHsp" style=""></span>&#956;U&#47;mL&#44; and high HOMA-IR values as those higher than 2&#46;5&#46; Both values are &#62;P95 of a representative sample of children and adolescents from the city of M&#233;rida &#40;CREDEFAR study&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">18</span></a></p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Echocardiographic measurement of epicardial adipose tissue</span><p id="par0050" class="elsevierStylePara elsevierViewall">A two-dimensional &#40;2D&#41; transthoracic echocardiogram using a standard procedure was performed&#44; with the patient in the left lateral decubitus position&#46; EAT thickness was measured by a pediatric echocardiographer using the procedure validated by Iacobellis et al&#46;<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">19</span></a></p><p id="par0055" class="elsevierStylePara elsevierViewall">EAT was identified as the echolucent space between the external wall of the myocardium and the visceral layer of the pericardium&#46; This thickness was measured perpendicularly on the free wall of the right ventricle at the end of systole in three cardiac cycles&#44; using a parasternal long or parasternal short axis view&#46; Measurement was taken on the free wall of the right ventricle for two reasons&#58; &#40;1&#41; this point is anatomically recognized as the one with the greatest epicardial fat thickness&#44; and &#40;2&#41; the parasternal long and parasternal short axes allow for more accurate measures of EAT on the right ventricle&#44; with an optimum slide orientation in each view&#46;<a class="elsevierStyleCrossRefs" href="#bib0245"><span class="elsevierStyleSup">20&#44;21</span></a></p></span></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Statistical analysis</span><p id="par0060" class="elsevierStylePara elsevierViewall">Continuous variables are given as mean<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>standard deviation&#44; and categorical variables as numbers and percentages&#46; A Chi-square test was used to assess potential sex-related differences between the groups and to establish associations between the categorical variables&#46; In order to determine the difference in the means of the continuous variables between subjects with less and more than two CRFs&#44; a Student&#39;s <span class="elsevierStyleItalic">t</span> test for independent data was used for normally distributed variables&#44; and a Mann&#8211;Whitney <span class="elsevierStyleItalic">U</span> test was used for non-normally distributed variables &#40;glucose&#44; total cholesterol&#44; LDL-C&#44; non-HDL-C&#44; insulin&#44; and HOMA-IR&#41;&#46; A receiver operating curve &#40;ROC&#41; was constructed to determine the cut-off point of EAT thickness for predicting the presence of two or more CRFs&#59; for this&#44; an area under the curve &#40;AUC&#41; of 1&#46;00 was considered as optimum&#44; an AUC ranging from 0&#46;90 to 0&#46;97 as very good&#44; an AUC from 0&#46;75 to 0&#46;90 as good&#44; and an AUC from 0&#46;60 to 0&#46;75 as fair&#46; AUCs under 0&#46;60 were considered to be a poorly valid test&#46; To estimate the optimum cut-off point from ROC&#44; the Youden index was calculated using the formula&#58; &#40;<span class="elsevierStyleItalic">J</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>sensitivity<span class="elsevierStyleHsp" style=""></span>&#43;<span class="elsevierStyleHsp" style=""></span>specificity<span class="elsevierStyleHsp" style=""></span>&#8722;<span class="elsevierStyleHsp" style=""></span>1<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>S<span class="elsevierStyleHsp" style=""></span>&#8722;<span class="elsevierStyleHsp" style=""></span>&#91;1<span class="elsevierStyleHsp" style=""></span>&#8722;<span class="elsevierStyleHsp" style=""></span>Sp&#93;&#41;&#46; A Pearson&#39;s correlation matrix was performed between the quantitative variables&#46; A linear regression analysis was also performed&#44; with EAT as the dependent variable&#44; to determine which variable had greater statistical significance&#44; as well as a logistic regression analysis with or without two or more CRFs as the dependent variable and EAT thickness and BMI as the independent variables&#44; in order to determine which of them had greater statistical significance for the presence of CRFs&#46; SPSS version 19&#46;0 for Windows was used for statistical analysis&#44; and a value of <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05 was considered statistically significant&#46;</p></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Results</span><p id="par0065" class="elsevierStylePara elsevierViewall">Seventy-seven children and adolescents were enrolled into the study&#46; The group with less than two CRFs consisted of 40 subjects&#44; 45&#37; girls and 55&#37; boys&#44; with a mean age of 12&#46;30<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>3&#46;14 years&#59; 32&#46;5&#37; were 6&#8211;9 years old&#44; 32&#46;5&#37; were 10&#8211;13 years old&#44; and 35&#37; were 14&#8211;18 years old&#46; Forty-five percent of the subjects were prepubertal &#40;Tanner stage I&#41;&#44; 35&#37; were undergoing puberty &#40;Tanner stages II&#8211;IV&#41;&#44; and 20&#37; were pubertal &#40;Tanner stage V&#41;&#46; The mean BMI was 22&#46;19<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>3&#46;95<span class="elsevierStyleHsp" style=""></span>kg&#47;m<span class="elsevierStyleSup">2</span>&#44; and the BMI <span class="elsevierStyleItalic">Z</span>-score was 0&#46;9<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>1&#46;15&#46; The group with less than two or more CRFs consisted of 37 subjects&#44; 51&#46;4&#37; girls and 48&#46;6&#37; boys&#44; with a mean age of 11&#46;60<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>3&#46;16 years&#59; 40&#46;5&#37; were 6&#8211;9 years old&#44; 37&#46;8&#37; were 10&#8211;13 years old&#44; and 21&#46;6&#37; were 14&#8211;18 years old&#59; 56&#46;8&#37; of these subjects were prepubertal&#44; 24&#46;3&#37; were undergoing puberty&#44; and 18&#46;9&#37; were pubertal&#59; the mean BMI was 25&#46;39<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>5&#46;00<span class="elsevierStyleHsp" style=""></span>kg&#47;m<span class="elsevierStyleSup">2</span>&#44; and the BMI <span class="elsevierStyleItalic">Z</span>-score was 1&#46;59<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;86&#46; There were no statistically significant differences between the groups in distribution by sex&#44; age&#44; pubertal stage&#44; family history of CRFs&#44; weight&#44; or height&#46; The BMI&#44; AC&#44; SBP&#44; and DBP were significantly higher in the group with more than two CRFs &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05 for SBP and <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;009 for all other variables&#41;&#46; There were 23 &#40;29&#46;9&#37;&#41; participants with normal weight&#44; 21 &#40;27&#46;3&#37;&#41; with overweight&#44; and 33 &#40;42&#46;9&#37;&#41; with obesity&#44; and a significantly greater frequency of participants with obesity was found in the group with two or more CRFs &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05&#41; &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0070" class="elsevierStylePara elsevierViewall">An analysis of the biochemical variables showed that the group of subjects with two or more CRFs had significantly higher values of blood glucose&#44; triglycerides &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05&#41;&#44; total cholesterol&#44; and LDL-C&#44; as well as Tg&#47;HDL-C&#44; TC&#47;HDL-C&#44; and LDL-C&#47;HDL-C ratios &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;005&#41;&#44; than the group with less than two CRFs&#44; while plasma HDL-C levels were significantly lower in the group of children and adolescents with two or more CRFs &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05&#41; &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#41;&#46; The most common risk factor was abdominal obesity &#40;50&#46;6&#37;&#41;&#44; followed by hypercholesterolemia &#40;27&#46;3&#37;&#41;&#44; high blood pressure &#40;24&#46;7&#37;&#41;&#44; decreased HDL-C &#40;24&#46;7&#37;&#41;&#44; and hypertriglyceridemia &#40;22&#46;1&#37;&#41;&#46; The least common risk factor was hyperglycemia &#40;13&#37;&#41;&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> shows that the group of subjects with two or more CRFs had greater EAT thickness &#40;3&#46;13 vs 2&#46;76<span class="elsevierStyleHsp" style=""></span>mm&#41;&#44; basal insulin &#40;16&#46;56 vs 10&#46;92<span class="elsevierStyleHsp" style=""></span>&#956;U&#47;mL&#41;&#44; and HOMA-IR &#40;4&#46;06 vs 2&#46;30&#41; values as compared to participants with less than two CRFs &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05&#41;&#46; Higher values of EAT &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41;&#44; insulin&#44; and HOMA-IR &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001 and <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05&#41; were also seen in the group with obesity&#44; abdominal obesity&#44; and HBP-preHBP&#46; HOMA-IR values were higher in participants with fasting hyperglycemia &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05&#41;&#46;</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0080" class="elsevierStylePara elsevierViewall">The ROC for the group of children and adolescents categorized based on the presence of CRFs had an AUC of 0&#46;64 &#40;95&#37; CI&#58; 0&#46;52&#8211;0&#46;77&#41;&#44; which rates the test as fair&#46; The cut-off point of EAT thickness as a predictor of two or more CRFs was 3&#46;17<span class="elsevierStyleHsp" style=""></span>mm &#40;<span class="elsevierStyleItalic">J</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;267&#41;&#44; with a 55&#46;6&#37; sensitivity and a 71&#46;1&#37; specificity &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>A&#41;&#46; The indirect relative risk or odds ratio of an individual having two or more risk factors if he&#47;she had an elevated EAT thickness&#44; taking as reference the cut-off point of 3&#46;17<span class="elsevierStyleHsp" style=""></span>mm obtained in the ROC analysis&#44; was 3&#46;1-fold greater than that of subjects with a lower value &#40;95&#37; CI&#58; 1&#46;174&#8211;8&#46;022&#59; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;020&#41;&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0085" class="elsevierStylePara elsevierViewall">A correlation analysis found that EAT&#44; measured in millimeters&#44; had a highly significant positive correlation to the BMI &#40;<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;561&#59; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41;&#44; SBP &#40;<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;256&#59; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;028&#41;&#44; plasma insulin levels &#40;<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;408&#59; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41;&#44; and HOMA-IR &#40;<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;325&#59; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;005&#41; &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46; EAT also positively correlated to AC &#40;<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;549&#59; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41;&#46; No correlation was found between EAT and lipid variables&#46; On the other hand&#44; a very significant correlation was seen between the BMI and SBP &#40;<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;423&#59; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41;&#44; insulin &#40;<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;460&#59; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41;&#44; and HOMA-IR &#40;<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;418&#59; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41; &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#41;&#46; Adjusted or controlled partial correlations were performed for the BMI&#44; and significant correlations of EAT with abdominal circumference&#44; SBP&#44; insulin&#44; and HOMA-IR were seen to lose their significance&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><elsevierMultimedia ident="fig0015"></elsevierMultimedia><p id="par0090" class="elsevierStylePara elsevierViewall">In the simple linear regression analysis with EAT thickness as the dependent variable&#44; SBP&#44; insulin&#44; HOMA-IR&#44; AC&#44; and the BMI were significant&#46; In the multiple linear regression analysis&#44; however&#44; SBP&#44; insulin&#44; HOMA-IR&#44; and AC lost statistical significance&#44; while BMI significance persisted &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;041&#41;&#44; being the variable which had the greatest impact on EAT thickness&#44; with an <span class="elsevierStyleItalic">R</span>-squared of 0&#46;352&#44; which meant that the BMI accounted for 35&#37; of EAT &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><p id="par0095" class="elsevierStylePara elsevierViewall">A logistic regression analysis with or without two or more CRFs as the dependent variable and EAT thickness and BMI as independent variables was performed to determine which of them had greater statistical significance for the presence of CRFs&#46; It was found that in the univariate analysis&#44; both EAT and BMI were significant&#46; In the multivariate analysis&#44; however&#44; EAT lost significance&#44; and it was therefore established that the BMI had a greater influence&#44; with an <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span> of 0&#46;175 and an indirect relative risk or odds ratio of 1&#46;20 &#40;95&#37; CI&#58; 1&#46;028&#8211;1&#46;406&#41; &#40;<a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0025"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Discussion</span><p id="par0100" class="elsevierStylePara elsevierViewall">The main findings of this study include&#58; &#40;1&#41; children and adolescents with two or more CRFs have greater EAT thickness as compared to the group with less than two CRFs&#59; &#40;2&#41; the cut-off point of EAT thickness that makes it possible to predict the presence of two or more CRFs is 3&#46;17<span class="elsevierStyleHsp" style=""></span>mm&#59; &#40;3&#41; a positive correlation exists between EAT thickness and other anthropometric &#40;BMI&#44; AC&#41;&#44; clinical &#40;SBP&#41;&#44; and biochemical &#40;insulin and HOMA-IR&#41; variables&#44; which is lost after the adjustment of correlation for the BMI&#59; &#40;4&#41; the BMI was the variable with the greatest impact on EAT thickness and the occurrence of two or more CRFs&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">No prior studies are available in Venezuela assessing EAT thickness in children and adolescents&#44; but in Latin America Cabrera-Rego et al&#46;<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">22</span></a> showed greater EAT thickness &#40;2&#46;76<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>1&#46;2 vs 1&#46;36<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;7<span class="elsevierStyleHsp" style=""></span>mm&#44; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41; in obese children and adolescents as compared to a control group&#46; These results agree with those of our study&#44; which showed that subjects with two or more CRFs had greater EAT values than those with less than 2 CRFs &#40;3&#46;13 vs 2&#46;76<span class="elsevierStyleHsp" style=""></span>mm&#41;&#44; and that obese children and adolescents had values significantly higher than non-obese subjects &#40;3&#46;43 vs 2&#46;61<span class="elsevierStyleHsp" style=""></span>mm&#41;&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">To the best our knowledge&#44; there have been no previous studies proposing cut-off points of EAT for predicting the presence of CRFs in a Latin American pediatric population&#46; In a European population&#44; Abaci et al&#46;<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">23</span></a> showed that EAT thickness greater than 4&#46;1<span class="elsevierStyleHsp" style=""></span>mm had a 90&#37; sensitivity and a 61&#37; specificity for predicting insulin resistance in children with obesity&#46; Cena et al&#46;<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">13</span></a> recently reported that&#44; in a population of 102 Italian male adolescents&#44; the optimum cut-off point of EAT thickness predicting for visceral obesity was 3&#46;2<span class="elsevierStyleHsp" style=""></span>mm&#46; This value is similar to the cut-off point of EAT found in our study as a predictor of the presence of two or more CRFs &#40;3&#46;17<span class="elsevierStyleHsp" style=""></span>mm&#41;&#46; These small differences were previously reported in an adult population&#44; and may be due to ethnic differences in body fat distribution&#46;<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">9</span></a></p><p id="par0115" class="elsevierStylePara elsevierViewall">Our results agree with those reported in other studies showing that EAT&#44; measured by echocardiography&#44; is related from childhood to the anthropometric&#44; clinical&#44; and biochemical components of MS&#46;<a class="elsevierStyleCrossRefs" href="#bib0200"><span class="elsevierStyleSup">11&#44;12&#44;24</span></a> Insulin resistance is considered the core of MS&#46; In this regard&#44; a two-fold greater release rate of fatty acids by epicardial adipocytes as compared to perirenal fat has been reported in animal models&#46; This suggests high lipolytic activity that is probably due to the reduced antilipolytic effect of insulin in this tissue and an increased expression of &#946;-adrenergic receptors&#44; especially &#946;-3 receptors&#44; whose stimulation activates lipolysis and increases the release of free fatty acids able to promote blood pressure increase through different pathways&#44; including adrenergic stimulation&#44; increased oxidative stress&#44; endothelial dysfunction&#44; and vascular cell growth&#46;<a class="elsevierStyleCrossRefs" href="#bib0270"><span class="elsevierStyleSup">25&#44;26</span></a> These observations explain the correlation between EAT and SBP&#44; and suggest that epicardial fat is a tissue with high insulin resistance&#46; This is supported by the fact that&#44; as in prior studies&#44; a significant correlation was seen between EAT thickness&#44; basal plasma insulin concentration&#44; and HOMA-IR&#46; In addition&#44; Manco et al&#46;<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">27</span></a> showed in obese prepubertal and pubertal children that at an early age&#44; EAT is a significant marker of increased insulin resistance&#46;</p><p id="par0120" class="elsevierStylePara elsevierViewall">The multiple linear regression analysis showed that the BMI was the variable that most influenced EAT thickness&#46; This results confirms that obesity is a factor predisposing to epicardial fat increase&#46;<a class="elsevierStyleCrossRefs" href="#bib0170"><span class="elsevierStyleSup">5&#44;28</span></a> As a novel contribution in this regard&#44; recent research has proposed EAT as a therapeutic target for different interventions in obese patients&#46;<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">13&#44;29</span></a> It should be emphasized that while AC is universally considered to be the most accessible visceral fat marker&#44; in this study the BMI had a greater influence on EAT thickness&#46; It has also been shown that the BMI was the variable with the greatest impact on CRF occurrence&#46; These findings agree with those reported by Schusterova et al&#46;<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">24</span></a> in children and adolescents with overweight and obesity&#46; These authors showed that the coefficients of correlation of EAT with various CRFs are similar to or better than those of AC&#44; but are not greater than those seen with the BMI&#46; This suggests that EAT thickness measured by echocardiography is not a stronger indicator of cardiometabolic risk in childhood than the BMI&#46;</p><p id="par0125" class="elsevierStylePara elsevierViewall">In conclusion&#44; in this group of children and adolescents&#44; the relationship of EAT to CRFs was found to be dependent on the BMI&#44; and the BMI was established as the dependent variable which most influenced EAT thickness&#46;</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Funding</span><p id="par0130" class="elsevierStylePara elsevierViewall">This study was conducted in part thanks to funding received from the <span class="elsevierStyleGrantSponsor" id="gs1">Council of Scientific&#44; Humanistic&#44; Technological&#44; and Art Development of Universidad de Los Andes</span> &#40;CDCHTA-ULA&#41; under projects M-1013-11-07-AA and ADG M-10&#44; and also from the <span class="elsevierStyleGrantSponsor" id="gs2">National Fund for Science&#44; Technology and Innovation</span> &#40;FONACIT&#41; of the Ministry of Popular Power for Science&#44; Technology and Innovation under project no&#46; 2012000970&#46;</p></span></span>"
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    "fechaRecibido" => "2015-06-15"
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      "en" => array:3 [
        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">To assess the relationship of epicardial adipose tissue &#40;EAT&#41; thickness with cardiometabolic risk factors &#40;CRFs&#41; in children and adolescents&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Seventy-seven subjects of both sexes aged 7&#8211;18 years were selected&#46; Medical history&#44; clinical parameters&#44; and glucose&#44; insulin&#44; and lipid levels were collected&#46; EAT thickness was measured using transthoracic echocardiography&#46; Study subjects were divided into two groups based on whether they had less than two or two or more CRFs&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The group with two or more CRFs had higher EAT thickness&#44; insulin&#44; and HOMA-IR values &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05&#41;&#46; EAT thickness showed a statistically significant positive correlation with body mass index &#40;BMI&#41; &#40;<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;561&#44; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41;&#44; waist circumference &#40;<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;549&#44; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41;&#44; systolic blood pressure &#40;SBP&#41; &#40;<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;256&#44; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;028&#41;&#44; insulin &#40;<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;408&#44; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41;&#44; and HOMA-IR &#40;<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;325&#44; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;005&#41;&#46; However&#44; these correlations were not significant after adjustment for BMI&#46; The cut-off point for EAT thickness as predictor of two or more CRFs was 3&#46;17<span class="elsevierStyleHsp" style=""></span>mm&#46; The risk &#40;odds ratio&#41; of having two or more CRFs if EAT thickness was &#62;3&#46;17<span class="elsevierStyleHsp" style=""></span>mm was 3&#46;1 &#40;95&#37; CI&#58; 1&#46;174&#8211;8&#46;022&#41;&#46; BMI was the independent variable that most affected EAT thickness and the presence of two or more CRFs&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">In this group of children and adolescents&#44; the relationship of EAT thickness with CRFs was found to be dependent on BMI&#46;</p></span>"
        "secciones" => array:4 [
          0 => array:2 [
            "identificador" => "abst0005"
            "titulo" => "Objective"
          ]
          1 => array:2 [
            "identificador" => "abst0010"
            "titulo" => "Methods"
          ]
          2 => array:2 [
            "identificador" => "abst0015"
            "titulo" => "Results"
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          3 => array:2 [
            "identificador" => "abst0020"
            "titulo" => "Conclusion"
          ]
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      "es" => array:3 [
        "titulo" => "Resumen"
        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Determinar la relaci&#243;n del espesor del tejido adiposo epic&#225;rdico &#40;TAE&#41; con factores de riesgo cardiometab&#243;lico &#40;FRC&#41; en ni&#241;os y adolescentes&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">M&#233;todos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Se seleccionaron 77 sujetos de ambos sexos entre 7 y 18 a&#241;os&#46; Se realiz&#243; anamnesis y evaluaci&#243;n de par&#225;metros cl&#237;nicos&#44; determinaci&#243;n de glucemia&#44; insulina y l&#237;pidos y se calcul&#243; el HOMA-IR&#46; Se determin&#243; el espesor del TAE mediante ecocardiograf&#237;a transtor&#225;cica&#46; Se formaron 2 grupos&#44; participantes con menos de 2 FRC &#40;cero o un FRC&#41; y participantes con 2 o m&#225;s FRC&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">El grupo con 2 o m&#225;s FRC present&#243; mayores valores de espesor del TAE&#44; insulina y HOMA-IR &#40;p<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;05&#41;&#46; El espesor del TAE mostr&#243; una correlaci&#243;n positiva estad&#237;sticamente muy significativa con el &#237;ndice de masa corporal &#40;IMC&#41; &#40;r<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;561&#59; p<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;0001&#41;&#44; la circunferencia abdominal &#40;r<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;549&#59; p<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;0001&#41;&#44; la presi&#243;n arterial sist&#243;lica &#40;PAS&#41; &#40;r<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;256&#59; p<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;028&#41;&#44; la insulina &#40;r<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;408&#59; p<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;0001&#41; y el HOMA-IR &#40;r<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;325&#59; p<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;005&#41;&#44; sin embargo&#44; estas correlaciones fueron no significativas al ajustar para el IMC&#46; El punto de corte para el espesor del TAE como predictor de 2 o m&#225;s FRC fue de 3&#44;17<span class="elsevierStyleHsp" style=""></span>mm&#46; El riesgo <span class="elsevierStyleItalic">&#40;odds ratio&#41;</span> de tener 2 o m&#225;s FRC si presenta un espesor de TAE<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>3&#44;17<span class="elsevierStyleHsp" style=""></span>mm fue de 3&#44;1 &#40;IC&#58; 1&#44;174&#8211;8&#44;022&#44; p<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;02&#41;&#46; El IMC fue la variable independiente que m&#225;s influy&#243; sobre los valores del espesor del TAE y la presencia de 2 o m&#225;s FRC&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusi&#243;n</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">En este grupo de ni&#241;os y adolescentes se encontr&#243; que la relaci&#243;n del TAE con los FRC es dependiente del IMC&#46;</p></span>"
        "secciones" => array:4 [
          0 => array:2 [
            "identificador" => "abst0025"
            "titulo" => "Objetivo"
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          1 => array:2 [
            "identificador" => "abst0030"
            "titulo" => "M&#233;todos"
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          2 => array:2 [
            "identificador" => "abst0035"
            "titulo" => "Resultados"
          ]
          3 => array:2 [
            "identificador" => "abst0040"
            "titulo" => "Conclusi&#243;n"
          ]
        ]
      ]
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    "NotaPie" => array:1 [
      0 => array:2 [
        "etiqueta" => "&#9734;"
        "nota" => "<p class="elsevierStyleNotepara" id="npar0035">Please cite this article as&#58; Reyes Y&#44; Paoli M&#44; Camacho N&#44; Molina Y&#44; Santiago J&#44; Lima-Mart&#237;nez MM&#46; Espesor del tejido adiposo epic&#225;rdico en ni&#241;os y adolescentes con factores de riesgo cardiometab&#243;lico&#46; Endocrinol Nutr&#46; 2016&#59;63&#58;70&#8211;78&#46;</p>"
      ]
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          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">ROC for establishing the cut-off point of EAT thickness for predicting two or more CRFs in this sample of children and adolescents&#46;</p>"
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        "etiqueta" => "Figure 2"
        "tipo" => "MULTIMEDIAFIGURA"
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          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Correlations of EAT with the BMI&#44; SBP&#44; insulin&#44; and HOMA-IR in the study subjects&#46;</p>"
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      2 => array:7 [
        "identificador" => "fig0015"
        "etiqueta" => "Figure 3"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
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          "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Correlations of the BMI with SBP&#44; insulin&#44; and HOMA-IR in the study subjects&#46;</p>"
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        "identificador" => "tbl0005"
        "etiqueta" => "Table 1"
        "tipo" => "MULTIMEDIATABLA"
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        "tabla" => array:3 [
          "leyenda" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Data are means<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>SD or <span class="elsevierStyleItalic">No&#46;</span> &#40;&#37;&#41;&#46;</p><p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">BMI&#44; body mass index&#59; DBP&#44; diastolic blood pressure&#59; SBP&#44; systolic blood pressure&#46;</p>"
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                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Variables&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">All &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>77&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Less than 2 CRFs &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>40&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Two or more CRFs &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>37&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Sex F&#47;M</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">37 &#40;48&#46;1&#41;&#47;40&#40;51&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">18 &#40;45&#46;0&#41;&#47;22 &#40;55&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">19 &#40;51&#46;4&#41;&#47;18 &#40;48&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Age &#40;years&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">11&#46;96<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>3&#46;15&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">12&#46;30<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>3&#46;14&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">11&#46;60<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>3&#46;16&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="4" 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="4" align="left" valign="top"><span class="elsevierStyleItalic">Age groups &#8211; No&#46; &#40;&#37;&#41;</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>6&#8211;9 years&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">28 &#40;36&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">13 &#40;32&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">15 &#40;40&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>10&#8211;13 years&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">27 &#40;35&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">13 &#40;32&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">14 &#40;37&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>14&#8211;18 years&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">22 &#40;28&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">14 &#40;35&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">8 &#40;21&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="4" 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="4" align="left" valign="top"><span class="elsevierStyleItalic">Pubertal stage</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>Prepubertal&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">39 &#40;50&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">18 &#40;45&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">21 &#40;56&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Undergoing puberty&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">23 &#40;29&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">14 &#40;35&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">9 &#40;24&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Pubertal&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">15 &#40;19&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">8 &#40;20&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">7 &#40;18&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="4" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></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="elsevierStyleItalic">Family hist&#46; CRFs &#8211; No&#46; &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">73 &#40;94&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">37 &#40;92&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">36 &#40;97&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Weight &#40;kg&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">51&#46;10<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>14&#46;84&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">48&#46;02<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>14&#46;19&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">54&#46;43<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>14&#46;99&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Height &#40;kg&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">146&#46;66<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>12&#46;80&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">146&#46;76<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>14&#46;43&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">146&#46;54<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>10&#46;96&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">BMI &#40;kg&#47;m</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">2</span></span><span class="elsevierStyleItalic">&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">23&#46;73<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>4&#46;74&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">22&#46;19<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>3&#46;95&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">25&#46;39<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>5&#46;00<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="4" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></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="elsevierStyleItalic">BMI Z-score</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;23<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>1&#46;07&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;90<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>1&#46;15&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;59<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;86<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Normal weight&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">23&#40;29&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">15 &#40;37&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">8 &#40;21&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Overweight&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">21 &#40;27&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">13 &#40;32&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">8 &#40;21&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Obesity&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">33 &#40;42&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">12 &#40;30&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">21 &#40;56&#46;8&#41;<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="4" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></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="elsevierStyleItalic">Waist &#40;cm&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">77&#46;64<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>11&#46;20&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">74&#46;05<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>9&#46;89&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">81&#46;53<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>11&#46;35<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">SBP &#40;mmHg&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">107&#46;31<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>9&#46;83&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">104&#46;55<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>9&#46;69&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">110&#46;29<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>9&#46;20<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">DBP &#40;mmHg&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">65&#46;70<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>7&#46;05&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">63&#46;94<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>7&#46;08&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">67&#46;60<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>6&#46;59<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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          "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Demographic and clinical data of patients categorized based on the presence of cardiometabolic risk factors &#40;CRFs&#41;&#46;</p>"
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        "tabla" => array:3 [
          "leyenda" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">Data are means<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>SD&#46;</p>"
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                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Variables&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Two or more CRFs &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>37&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Blood glucose &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">83&#46;47<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>9&#46;29&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">103&#46;18<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>41&#46;12<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Triglycerides &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">71&#46;42<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>43&#46;30&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">93&#46;48<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>48&#46;09<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Total cholesterol &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">144&#46;37<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>31&#46;64&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">201&#46;43<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>83&#46;44<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">LDL-C &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">87&#46;62<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>30&#46;32&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">144&#46;27<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>74&#46;65<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">HDL-C &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">42&#46;22<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>5&#46;14&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">38&#46;43<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>7&#46;34<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Non-HDL-C &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">102&#46;15<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>32&#46;82&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">163&#46;00<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>81&#46;20<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Tg&#47;HDL-C&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;73<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>1&#46;14&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&#46;49<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>1&#46;34<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">TC&#47;HDL-C&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">5&#46;28<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>1&#46;99<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">LDL-C&#47;HDL-C&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;78<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>1&#46;82<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
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          "leyenda" => "<p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">Data are means<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>SD&#46;</p>"
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                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Variables&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Less than 2 CRFs &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>40&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Two or more CRFs &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>37&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">EAT &#40;mm&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;76<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;78&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3&#46;13<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;73<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Insulin &#40;&#956;U&#47;mL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">10&#46;92<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>10&#46;17&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">16&#46;56<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>11&#46;57<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">HOMA-IR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;30<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>2&#46;38&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">4&#46;06<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>2&#46;79<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="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  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">No obesity &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>44&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Obesity &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>33&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">EAT &#40;mm&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;61<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;65&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3&#46;43<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;70<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Insulin &#40;&#956;U&#47;mL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">10&#46;05<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>9&#46;17&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">18&#46;49<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>11&#46;92<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">HOMA-IR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;34<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>2&#46;17&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">4&#46;24<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>3&#46;04<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="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  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">No abdominal ob&#46; &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>38&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Abdominal ob&#46; &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>39&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">EAT &#40;mm&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;58<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;59&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3&#46;32<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;78<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Insulin &#40;&#956;U&#47;mL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">8&#46;58<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>5&#46;25&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">18&#46;59<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>13&#46;15<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">HOMA-IR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;07<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>1&#46;57&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">4&#46;20<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>3&#46;19<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="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  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">No HBP &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>58&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">HBP-preHBP &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>19&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">EAT &#40;mm&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;78<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;73&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3&#46;45<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;70<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">&#42;&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Insulin &#40;&#956;U&#47;mL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">12&#46;48<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>11&#46;56&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">17&#46;04<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>9&#46;21<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">HOMA-IR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;81<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>2&#46;70&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">4&#46;14<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>2&#46;59<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="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  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Normal blood glucose &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>67&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">High blood glucose &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>10&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">EAT &#40;mm&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;98<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;80&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;68<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;57&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Insulin &#40;&#956;U&#47;mL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">13&#46;56<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>11&#46;39&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">13&#46;78<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>9&#46;83&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">HOMA-IR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;84<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>2&#46;57&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">5&#46;23<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>2&#46;97<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">&#42;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="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  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">No dyslipidemia &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>35&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Dyslipidemia &#40;n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>42&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">EAT &#40;mm&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3&#46;01<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;87&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;88<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>0&#46;69&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Insulin &#40;&#956;U&#47;mL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">13&#46;72<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>11&#46;58&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">13&#46;48<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>10&#46;92&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">HOMA-IR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;94<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>2&#46;70&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3&#46;30<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>2&#46;76&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
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          "en" => "<p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">Epicardial adipose tissue &#40;EAT&#41;&#44; basal insulin&#44; and HOMA-IR values in patients categorized based on the presence of cardiovascular risk factors &#40;CRFs&#41;&#46;</p>"
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                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td-with-role" title="table-head ; entry_with_role_rowhead " align="left" valign="top" scope="col">Independent variables&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col">Simple&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col">Multiple&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span> value&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span> value&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></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">SBP &#40;mmHg&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;028&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;877&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Insulin &#40;&#956;U&#47;mL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;0001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;154&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">HOMA-IR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;005&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;345&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
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  "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173509316000271?idApp=UINPBA00004N"
]

Article information

ISSN: 21735093
Original language: English

DOI:10.1016/j.endoen.2016.02.005

The statistics are updated each day

Year/Month	Html	Pdf	Total

2024 November	3	0	3
2024 October	28	3	31
2024 September	26	5	31
2024 August	30	2	32
2024 July	42	3	45
2024 June	11	3	14
2024 May	15	7	22
2024 April	17	4	21
2024 March	39	6	45
2024 February	27	10	37
2024 January	27	0	27
2023 December	25	11	36
2023 November	36	11	47
2023 October	41	9	50
2023 September	24	1	25
2023 August	16	4	20
2023 July	26	10	36
2023 June	14	4	18
2023 May	17	4	21
2023 April	10	5	15
2023 March	14	4	18
2023 February	15	3	18
2023 January	16	5	21
2022 December	19	9	28
2022 November	28	7	35
2022 October	23	9	32
2022 September	17	23	40
2022 August	29	21	50
2022 July	31	7	38
2022 June	48	5	53
2022 May	49	4	53
2022 April	21	13	34
2022 March	27	4	31
2022 February	21	4	25
2022 January	50	7	57
2021 December	64	8	72
2021 November	31	11	42
2021 October	45	12	57
2021 September	16	12	28
2021 August	29	6	35
2021 July	27	8	35
2021 June	27	13	40
2021 May	28	7	35
2021 April	61	15	76
2021 March	48	9	57
2021 February	38	12	50
2021 January	29	5	34
2020 December	26	14	40
2020 November	31	12	43
2020 October	20	5	25
2020 September	17	10	27
2020 August	37	9	46
2020 July	31	9	40
2020 June	27	10	37
2020 May	35	5	40
2020 April	19	2	21
2020 March	21	9	30
2020 February	23	8	31
2020 January	22	5	27
2019 December	25	6	31
2019 November	21	12	33
2019 October	23	4	27
2019 September	23	4	27
2019 August	20	3	23
2019 July	27	24	51
2019 June	35	43	78
2019 May	77	48	125
2019 April	47	16	63
2019 March	16	3	19
2019 February	18	14	32
2019 January	23	1	24
2018 December	17	4	21
2018 November	20	5	25
2018 October	26	6	32
2018 September	26	9	35
2018 August	2	3	5
2018 July	13	3	16
2018 June	31	9	40
2018 May	16	1	17
2018 April	10	3	13
2018 March	13	2	15
2018 February	11	1	12
2018 January	10	0	10
2017 December	11	0	11
2017 November	11	0	11
2017 October	9	6	15
2017 September	14	1	15
2017 August	16	0	16
2017 July	13	1	14
2017 June	27	14	41
2017 May	26	2	28
2017 April	19	3	22
2017 March	28	32	60
2017 February	45	7	52
2017 January	6	3	9
2016 December	25	10	35
2016 November	56	5	61
2016 October	44	5	49
2016 September	33	2	35
2016 August	22	6	28
2016 May	0	1	1

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Now is Endocrinología, Diabetes y Nutrición (English ed.). More information

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Now is Endocrinología, Diabetes y Nutrición (English ed.). More information

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