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Clinical analysis of the relationship between cystatin C and metabolic syndrome in the elderly
Análise clínica para a relação entre a cistatina C e a síndrome metabólica nos idosos
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Compared with the control group, the MetD and MetS groups had higher MetS component scores and cystatin C concentrations (all p<0.05). In comparison with MetD, the MetS group had higher MetS component scores and cystatin C concentrations (all p<0.05). As MetS component scores rose, cystatin C concentrations also increased. 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array:3 [ "nombre" => "Caixia" "apellidos" => "Liu" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] ] "afiliaciones" => array:2 [ 0 => array:3 [ "entidad" => "Department of Cardiology, The Second Hospital of Shandong University, Jinan, Shandong, China" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Medical College, Shandong University, Jinan, Shandong, China" "etiqueta" => "b" "identificador" => "aff0010" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "pt" => array:1 [ "titulo" => "Análise clínica para a relação entre a cistatina C e a síndrome metabólica nos idosos" ] ] "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" => 946 "Ancho" => 1630 "Tamanyo" => 74722 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Comparison of MetS component scores and cystatin C concentrations between groups. Compared with the control group, the MetD and MetS groups had higher MetS component scores and cystatin C concentrations (all p<0.05). In comparison with MetD, the MetS group had higher MetS component scores and cystatin C concentrations (all p<0.05). As MetS component scores rose, cystatin C concentrations also increased. MetD: metabolic disturbances; MetS: metabolic syndrome.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Cystatin C (cysteine protease inhibitor C) is a member of the protease inhibitor superfamily, consisting of 122 amino acids, and is a low molecular weight alkaline protein. Various studies<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1–3</span></a> have revealed that cystatin C is not only a more sensitive indicator of renal function than creatinine or creatinine clearance but is also an independent and strong predictor of cardiovascular events, diabetes and all-cause mortality. Recent research has shown that cystatin C is closely associated with the inflammatory process and other inflammation factors.<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1,4</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Metabolic syndrome (MetS) is a clinical entity characterized by abdominal obesity, hyperglycemia, hypertension, and dyslipidemia. Each of the components has been recognized as a risk factor for cardiovascular events. It is reported that more than 20% of the elderly suffer from MetS in China and the prevalence of MetS in the elderly in the United States has reached 43.5%. A prospective clinical study has demonstrated that serum cystatin C concentration has a strong independent association with cardiovascular events. MetS, as the most important risk factor for cardiovascular disease, carries a high risk of renal dysfunction, and abnormal renal function also has a close correlation with cardiovascular risk. As a marker of renal function, cystatin C may be closely related to MetS.<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1,3,5</span></a> However, the pathogenesis of MetS has not been fully determined. The elderly have a high incidence of cardiovascular and kidney disease, so this study set out to analyze clinical data on MetS, to investigate whether there is a relationship between cystatin C and MetS in the elderly, and to discuss its possible pathogenesis and clinical importance.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Study population and diagnostic criteria</span><p id="par0015" class="elsevierStylePara elsevierViewall">A total of 380 consecutive subjects were prospectively recruited between August 2009 and July 2012 from the Second Hospital of Shandong University and Qilu Hospital of Shandong University. According to the International Diabetes Federation (IDF) criteria,<a class="elsevierStyleCrossRefs" href="#bib0030"><span class="elsevierStyleSup">6,7</span></a> MetS is defined as central obesity (waist circumference ≥90 cm for Chinese men and ≥80 cm for Chinese women) plus any two of the following: (1) triglycerides (TG) ≥1.7 mmol/l or specific treatment for this lipid abnormality; (2) high-density lipoprotein (HDL-C) levels <1.0 mmol/l in men and <1.3 mmol/l in women or specific treatment for this lipid abnormality; (3) systolic blood pressure (SBP) ≥130 mmHg or diastolic blood pressure (DBP) ≥85 mmHg or treatment of previously diagnosed hypertension; and (4) fasting plasma glucose (FPG) ≥5.6 mmol/l or previously diagnosed type 2 diabetes. The criteria for a diagnosis of metabolic disturbance (MetD) is at least one of the diagnostic criteria for MetS as listed above. The definition of elderly was taken as 60 years of age or older. All diagnoses of MetS or MetD were supported by medical history, physical examination and laboratory tests. Patients with any of the following conditions were excluded from the study: infectious diseases, autoimmune disease, severe chronic disease such as advanced liver cirrhosis or cancer, renal dysfunction or use of hormone. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki. The study protocol was approved by the Clinical Research Ethics Committee of the Secondary Hospital of Shandong University and written informed consent was obtained from all participants.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Groups and study design</span><p id="par0020" class="elsevierStylePara elsevierViewall">Subjects were divided into three groups according to the diagnosis of MetS and MetD: the MetS group included 135 patients, 64 male and 71 female, mean age 69.18±6.30 (60–82) years; the MetD group had 142 patients, 65 male and 77 female, mean age 70.05±6.64 (60–86) years; and the control group had 103 elderly individuals deemed healthy after examination, including 41 males and 62 females, with a mean age of 69.39±6.58 (60–85) years. There were no statistically significant differences (p>0.05) in age, gender or etiological composition between the three groups.</p><p id="par0025" class="elsevierStylePara elsevierViewall">On the basis of their MetS score, determined as the number of metabolic syndrome components described by the IDF definition,<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a> each group was also subdivided into subgroups as follows: score-0 subgroup, subjects with no abnormal component; score-1 subgroup, subjects with one abnormal component, and so on, making a total of five subgroups.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Biochemical assessment</span><p id="par0030" class="elsevierStylePara elsevierViewall">A 5-ml peripheral vein blood sample was obtained from all participants early in the day after a 12-h fast, immediately transferred to a glass tube containing disodium ethylenediaminetetraacetic acid (EDTA), centrifuged for 10 min at 3000 rpm, separated into aliquots, and then stored at −80<span class="elsevierStyleHsp" style=""></span>°C. Cystatin C was measured by means of a particle-enhanced turbidimetric immunoassay with commercial kits (Beijing Leadman Biochemistry Co., Ltd., Beijing, China). Its normal reference value is 0.55–1.05 mg/l. FPG, hemoglobin A1c (HbA1c), total cholesterol (TC), LDL-C, HDL-C, TG, blood urea nitrogen and serum creatinine (Cr) were measured using an automatic biochemical analyzer (Hitachi 7600, Tokyo, Japan) with an enzymatic method in all subjects. Microalbuminuria (MAU) in early morning urine was assessed by rapid immunoturbidimetry using a DCA 2000 analyzer (Bayer Diagnostics, München, Germany). Estimated glomerular filtration rate (eGFR) was calculated by a modified MDRD equation: eGFR (ml/min per 1.73 m<span class="elsevierStyleSup">2</span>)=175×plasma Cr (mg/dl)<span class="elsevierStyleSup">−1.234</span>×age (in years)<span class="elsevierStyleSup">−0.179</span>×0.79 (if female).<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a> All measurements were approved according to the quality control standards of the laboratory.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Statistical analysis</span><p id="par0035" class="elsevierStylePara elsevierViewall">Continuous variables were presented as mean ± SD and categorical variables were expressed as percentages. Measurement variables were compared using one-way ANOVA and numerical variables were compared with the chi-square test. The significance of associations between variables was assessed by partial correlation analysis after adjusting for classical risk factors (age and gender). Predictors of MetS were determined by multivariate regression analysis. The association between variables and the occurrence of MetS was represented by odds ratios (OR) and 95% confidence intervals (CI). SPSS 19.0 (SPSS Inc., Chicago, IL, USA) was used for all calculations. A value of p<0.05 was considered significant.</p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Results</span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Clinical characteristics of the study population</span><p id="par0040" class="elsevierStylePara elsevierViewall">As shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>, there were no differences in age or gender ratio between the MetS, MetD and control groups (p>0.05). There were significant differences in weight-related indicators (body mass index [BMI], waist circumference, waist–hip ratio and waist–height ratio), blood glucose parameters (FPG, HbA1c), blood lipids (LDL-C, TG and HDL-C), blood pressure (SBP, DBP and pulse pressure), renal function (Cr, eGFR and MAU) and cystatin C between the three groups (p<0.05 or p<0.01).</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Relationship between metabolic syndrome scores and cystatin C (<a class="elsevierStyleCrossRef" href="#fig0005">Figure 1</a>)</span><p id="par0050" class="elsevierStylePara elsevierViewall">The higher the MetS component scores, the higher the serum cystatin C concentration in these patients. In comparison with the control group, the MetS and MetD groups had significantly higher cystatin C concentrations (p<0.05 or p<0.01). Compared with MetD group, the MetS group had significantly cystatin C (p<0.05 or p<0.01).</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Correlation analysis for serum cystatin C levels and MetS components (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>)</span><p id="par0060" class="elsevierStylePara elsevierViewall">After adjusting for age and gender, the results of partial correlation analysis for a single factor showed that serum cystatin C concentrations in the MetS group were closely associated with (1) the body weight-related indicators BMI, waist–hip ratio, waist circumference and waist–height ratio, with <span class="elsevierStyleItalic">r</span> values all >0.300 (all p<0.05); (2) TG levels (<span class="elsevierStyleItalic">r</span>=0.285, p=0.040) but not LDL-C levels (<span class="elsevierStyleItalic">r</span>=0.283, p=0.058), and negatively associated with HDL-C levels (<span class="elsevierStyleItalic">r</span>=−0.219, p=0.046); (3) FPG and HbA1c (<span class="elsevierStyleItalic">r</span>=0.442, p=0.000; <span class="elsevierStyleItalic">r</span>=0.371, p=0.045, respectively); and (4) SBP, DBP and pulse pressure (<span class="elsevierStyleItalic">r</span>=0.464, p=0.004; <span class="elsevierStyleItalic">r</span>=0.322, p=0.029; <span class="elsevierStyleItalic">r</span>=0.376, p=0.006, respectively).</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Multivariate logistic regression analysis of risk factors for metabolic syndrome (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>)</span><p id="par0070" class="elsevierStylePara elsevierViewall">Multivariate stepwise regression analysis was performed to determine independent risk factors for MetS, with age, gender, and other factors including BMI, waist–hip ratio, waist circumference, waist–height ratio, FPG, HbA1c, LDL-C, TG, Cr, eGFR, MAU, SBP, DBP and pulse pressure identified in univariate analysis as independent variables. In this model, the presence or absence of MetS was taken as a dependent variable. All the independent variables were put into the logistic regression model. The analysis demonstrated that cystatin C (OR=2.164, 95% CI=1.136–8.259, p=0.002), waist–height ratio (OR=3.406, 95% CI=1.965–15.098, p=0.000), waist circumference (OR=2.951, 95% CI=1.351–9.270, p=0.008), TG (OR=1.526, 95% CI=0.112–0.515, p=0.004), FPG (OR=1.883, 95% CI=0.267–2.799, p=0.012), SBP (OR=2.105, 95% CI=1.218–9.772, p=0.047) and pulse pressure (OR=1.747, 95% CI=0.198–2.545, p=0.000) entered the regression equation and were then independently associated with MetS.</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia></span></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Discussion</span><p id="par0075" class="elsevierStylePara elsevierViewall">As the most important etiological factor of cardiovascular disease, MetS is probably intimately associated with cystatin C. In our study population, the greater the number of MetS components, the higher were the serum cystatin C levels. So cystatin C may be able to predict the risk of cardiovascular events.<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a></p><p id="par0080" class="elsevierStylePara elsevierViewall">Central obesity is a key factor in the occurrence and development of MetS.<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> However, some anthropometric parameters of central obesity remain controversial. Although BMI is widely applied in the assessment of overweight and obesity, it does not distinguish fat from muscle or different fat distribution.<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> The main limitation of the waist–hip ratio is that both waist and hip circumference can change with weight variation and as a consequence alterations in the ratio are frequently small.<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> Waist circumference is a sensitive indicator of central obesity; it not only reflects visceral fat content but is also the principal parameter for predicting obesity health-related risk. Waist circumference is also strongly related to central obesity. Nevertheless, it does not take into account differences in individual stature.<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> A meta-analysis has shown that waist–height ratio is a better screening tool for cardiometabolic outcomes than other indicators of somatometric measurement, using receiver operating characteristic analysis as an indicator of sensitivity, with a ranking order of areas under the curve for predictive ability of the anthropometric indices of waist–height ratio>waist circumference>waist–hip ratio>BMI.<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">11</span></a> Multivariate regression analysis in this study confirmed that waist–height ratio and waist circumference had a significant correlation with MetS in women and are simple and convenient measures.</p><p id="par0085" class="elsevierStylePara elsevierViewall">It has been shown that cystatin C is closely linked to adipose tissue. Preadipocytes differentiated in vitro can express and release cystatin C; subcutaneous and omental fatty tissue overexpress cystatin C in vivo. Cystatin C produced by adipose tissue may be a fat-derived secretory adipocytokine.<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> It not only has the potential to affect adipose tissue and vascular homeostasis through local and/or systemic inhibition of cathepsins but also affects the functions of adipose tissue and induces obesity-linked complications.<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a></p><p id="par0090" class="elsevierStylePara elsevierViewall">Clinical data have demonstrated that serum cystatin C levels are closely connected to LDL-C and TG in patients with coronary heart disease.<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> Univariate analysis in this study showed cystatin C was positively correlated with TG and LDL-C, and negatively correlated with HDL-C. However, multivariate analysis disclosed that TG was the only lipid variable that entered the regression equation. This is probably linked to the characteristics of hyperlipidemia in China, where there is less hypercholesterolemia, mainly low HDL-C and hypertriglyceridemia. In particular, among elderly patients with MetS, hypertriglyceridemia accounted for 37.4% of lipid metabolic abnormalities, while decreased HDL-C accounted for only 2.6%. Multivariate regression analysis in the Western New York Study indicated that cystatin C is the strongest independent risk factor for hyperglycemia,<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> its concentration increasing before the onset of clinical diabetes. In comparison with healthy adults, cystatin C was associated with a threefold excess risk of progression to pre-diabetes in this population,<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> and cystatin C and FPG were shown to be closely connected. Kestenbaum et al. found, in long-term follow-up, that after adjusting for confounding factors, cystatin C concentration in different ethnic populations is independently correlated with blood pressure.<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> Data from the Heart and Soul Study revealed SBP and pulse pressure were linearly associated with cystatin C concentrations.<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a> The univariate correlation analysis in this study showed that SBP and pulse pressure had a closer association with cystatin C than DBP. These findings are probably relevant to features of hypertension in the elderly.</p><p id="par0095" class="elsevierStylePara elsevierViewall">The mechanism of cystatin C's association with MetS remains unclear. Possibilities include the following.<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1,16–18</span></a> (1) Impaired renal function: each component of MetS may lead to renal function impairment.<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a> In our study, the MetS group had significantly higher Cr, eGFR and MAU values than the other groups. When renal function is impaired, ultrafiltration rate and loss of charge selectivity may contribute to the increased serum cystatin C concentrations in MetS patients.<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> (2) Cystatin C participates in the process of cell apoptosis and has direct toxic effects on cells. (3) Cystatin C levels correlate significantly with insulin resistance.<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> (4) Cystatin C is intimately linked to inflammatory and procoagulant factors,<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> including homocysteine, C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), intercellular adhesion molecule-1, fibrinogen, and others. Moreover, cystatin C is independently related to CRP.<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1,4</span></a> In addition, cystatin C and its fragments may affect the phagotrophic and chemotactic functions of granulocytes, and participate in the inflammatory process.<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1,20</span></a> (5) Cystatin C is relevant to hypermetabolism.<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> (6) Cystatin C may induce MetS by an oxidative stress mechanism.<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a></p><p id="par0100" class="elsevierStylePara elsevierViewall">We acknowledge several limitations in this study. First, our sample size, although small, was sufficient to display differences between the MetS group and the control group, but further studies with larger cohorts should be performed to confirm these results. In addition, some inflammatory markers such as CRP, IL-6 and TNF-α were not assessed in this study to further elucidate the pathogenesis of MetS. Finally, we did not divide the patients with MetS score-4 and MetS score-5 into two groups because of the limited numbers in the two groups.</p><p id="par0105" class="elsevierStylePara elsevierViewall">In conclusion, cystatin C is not only closely related to MetS in the elderly but is also intimately linked to the components of MetS. This study indicates that paying more attention to serum cystatin C levels in elderly patients at high risk for MetS has important theoretical and clinical implications for the prevention of MetS in the elderly. The generation rate of cystatin C is stable, not affected by factors such as gender, age, diet, bilirubin, or hemolysis. Monitoring dynamic changes in cystatin C levels may help in predicting the occurrence, development and prognosis of MetS in the elderly.</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Ethical disclosures</span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Protection of human and animal subjects</span><p id="par0110" class="elsevierStylePara elsevierViewall">The authors declare that no experiments were performed on humans or animals for this study.</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Confidentiality of data</span><p id="par0115" class="elsevierStylePara elsevierViewall">The authors declare that no patient data appear in this article.</p></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Right to privacy and informed consent</span><p id="par0120" class="elsevierStylePara elsevierViewall">The authors declare that no patient data appear in this article.</p></span></span><span id="sec0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Conflicts of interest</span><p id="par0125" class="elsevierStylePara elsevierViewall">The authors have no conflicts of interest to declare.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:11 [ 0 => array:2 [ "identificador" => "xres380834" "titulo" => array:5 [ 0 => "Abstract" 1 => "Objective" 2 => "Methods" 3 => "Results" 4 => "Conclusion" ] ] 1 => array:2 [ "identificador" => "xpalclavsec359647" "titulo" => "Keywords" ] 2 => array:2 [ "identificador" => "xres380835" "titulo" => array:5 [ 0 => "Resumo" 1 => "Objetivo" 2 => "Métodos" 3 => "Resultados" 4 => "Conclusão" ] ] 3 => array:2 [ "identificador" => "xpalclavsec359646" "titulo" => "Palavras-chave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Methods" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Study population and diagnostic criteria" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Groups and study design" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Biochemical assessment" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Statistical analysis" ] ] ] 6 => array:3 [ "identificador" => "sec0035" "titulo" => "Results" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0040" "titulo" => "Clinical characteristics of the study population" ] 1 => array:2 [ "identificador" => "sec0045" "titulo" => "Relationship between metabolic syndrome scores and cystatin C (Figure 1)" ] 2 => array:2 [ "identificador" => "sec0050" "titulo" => "Correlation analysis for serum cystatin C levels and MetS components (Table 2)" ] 3 => array:2 [ "identificador" => "sec0055" "titulo" => "Multivariate logistic regression analysis of risk factors for metabolic syndrome (Table 3)" ] ] ] 7 => array:2 [ "identificador" => "sec0060" "titulo" => "Discussion" ] 8 => array:3 [ "identificador" => "sec0065" "titulo" => "Ethical disclosures" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0070" "titulo" => "Protection of human and animal subjects" ] 1 => array:2 [ "identificador" => "sec0075" "titulo" => "Confidentiality of data" ] 2 => array:2 [ "identificador" => "sec0080" "titulo" => "Right to privacy and informed consent" ] ] ] 9 => array:2 [ "identificador" => "sec0085" "titulo" => "Conflicts of interest" ] 10 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2013-10-18" "fechaAceptado" => "2014-01-02" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec359647" "palabras" => array:5 [ 0 => "Metabolic syndrome" 1 => "Cystatin C" 2 => "Elderly" 3 => "Inflammation" 4 => "Obesity" ] ] ] "pt" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palavras-chave" "identificador" => "xpalclavsec359646" "palabras" => array:5 [ 0 => "Síndrome metabólica" 1 => "Cistatina C" 2 => "Idosos" 3 => "Inflamação" 4 => "Obesidade" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:2 [ "titulo" => "Abstract" "resumen" => "<span class="elsevierStyleSectionTitle" id="sect0010">Objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Studies have shown that both cystatin C and metabolic syndrome (MetS) are associated with inflammation. We set out to investigate the correlation between serum cystatin C levels and MetS in the elderly.</p> <span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">This prospective study was conducted in 380 elderly individuals, including 135 patients with MetS, 142 patients with metabolic disturbance (MetD), and 103 healthy elderly individuals (control group). Waist–hip ratio, waist circumference, waist–height ratio, body mass index (BMI), fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), high-density lipoprotein (HDL-C), systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure and cystatin C were measured and their mutual relations were analyzed.</p> <span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The higher the MetS scores, the higher the serum cystatin C concentration in these patients. Serum cystatin C concentration was closely related to waist–hip ratio, waist circumference, waist–height ratio, BMI, TG, FPG, and blood pressure, not related to LDL-C levels, and negatively correlated with HDL-C levels. Logistic regression analysis indicated that cystatin C, waist–height ratio, waist circumference, FPG, TG, SBP and pulse pressure were significantly associated with MetS (OR between cystatin C and MetS 2.164, 95% CI 1.136–8.259).</p> <span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Cystatin C was significantly associated with MetS in the elderly. As MetS scores rose, serum cystatin C levels increased.</p>" ] "pt" => array:2 [ "titulo" => "Resumo" "resumen" => "<span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Alguns estudos demonstraram que tanto a cistatina C como a síndrome metabólica (SM) estão associadas à inflamação. Procuramos investigar a correlação entre os níveis séricos da cistatina C e a SM nos idosos.</p> <span class="elsevierStyleSectionTitle" id="sect0040">Métodos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Este estudo prospetivo foi realizado em 380 idosos, incluindo 135 doentes com SM, 142 doentes com alterações metabólicas (AM) e 103 idosos saudáveis num grupo de controlo corrente. Foram medidos a relação cintura-quadril, o perímetro abdominal, a razão cintura-estatura, o índice da massa corporal (IMC), glicemia em jejum, a hemoglobina glicada (HbA1c), o colesterol de lipoproteína de baixa densidade (colesterol-DL), os triglicéridos (TG),o colesterol de lipoproteína de alta densidade (colesterol-HDL), a pressão arterial sistólica (PAS), a pressão arterial diastólica (PAD), a pressão do pulso e a cistatina C e foram avaliadas as suas relações mútuas.</p> <span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">1. Como os <span class="elsevierStyleItalic">scores</span> dos componentes da SM aumentaram, os níveis da cistatina C subiram nestes doentes. Quanto mais elevados foram os <span class="elsevierStyleItalic">scores</span> da SM, mais elevada foi a concentração sérica de cistatina C nestes doentes. 2. A concentração sérica de cistatina C foi estreitamente relacionada com a razão cintura-quadril, com o perímetro abdominal, com a razão cintura-estatura, com o IMC, com os TG, com a glicemia em jejum e com a pressão arterial, mas não associada aos níveis de colesterol-LDL e negativamente correlacionada com os níveis de colesterol-HDL. 3. A análise de regressão logística indicou que a cistatina C, a razão cintura-estatura, o perímetro abdominal, a glicemia em jejum, os TG, a PAS e a pressão do pulso foram significativamente associados à SM, ao valor da OR entre a cistatina C e a SM foi de 2,164 (95% IC=1,136-8,259).</p> <span class="elsevierStyleSectionTitle" id="sect0050">Conclusão</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">A cistatina C foi significativamente associada com a SM nos idosos. Como os <span class="elsevierStyleItalic">scores</span> da SM subiram, os níveis séricos de cistatina C aumentaram.</p>" ] ] "multimedia" => array:4 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 946 "Ancho" => 1630 "Tamanyo" => 74722 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Comparison of MetS component scores and cystatin C concentrations between groups. Compared with the control group, the MetD and MetS groups had higher MetS component scores and cystatin C concentrations (all p<0.05). In comparison with MetD, the MetS group had higher MetS component scores and cystatin C concentrations (all p<0.05). As MetS component scores rose, cystatin C concentrations also increased. MetD: metabolic disturbances; MetS: metabolic syndrome.</p>" ] ] 1 => array:7 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:3 [ "leyenda" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">BMI: body mass index; Cr: serum creatinine; DBP: diastolic blood pressure; eGFR: estimated glomerular filtration rate; FPG: fasting plasma glucose; HbA1c: hemoglobin A1c; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; MAU: microalbuminuria; MetS: metabolic syndrome; MetD: metabolic disturbance; SBP: systolic blood pressure; TG: triglycerides; WC: waist circumference.</p><p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Compared with control group:</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Variables \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Controls (n=103) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">MetD (n=142) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">MetS (n=135) \t\t\t\t\t\t\n \t\t\t\t</td></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age (years) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">69.39±6.58 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">70.05±6.64 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">69.18±6.30 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Gender (female/male) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41/62 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65/77 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">64/71 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">BMI (kg/m<span class="elsevierStyleSup">2</span>) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">24.82±1.60 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27.61±3.66<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">*</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29.07±4.84<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">##</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">WC (cm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">83.97±8.05 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">88.90±13.47<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">*</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">98.54±18.25<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">##</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Waist–hip ratio \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.85±0.06 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.98±0.08<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">*</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.04±0.09<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">##</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Waist–height ratio \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.52±0.08 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.60±0.08 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.67±0.09 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">FPG (mmol/l) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.24±1.05 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.09±2.01<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.63±2.37<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">##</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HbA1c \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.83±0.90 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.56±1.61<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.30±2.40<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">##</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LDL-C (mmol/l) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.38±1.04 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.58±1.14<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.40±1.21<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">##</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">TG (mmol/l) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.26±0.40 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.20±0.83<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">*</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.95±0.68<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">*</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">#</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HDL (mmol/l) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.35±0.47 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.21±0.39<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">*</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.04±0.30<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">*</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">##</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Cr (μmol/l) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">55.72±17.61 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">85.60±24.86<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">108.77±38.59<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">##</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">MAU (mg/l) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20.08±5.13 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27.79±5.59<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">38.75±9.90<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">##</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">eGFR \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">89.85±12.06 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">77.08±16.67<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">64.80±14.63<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">##</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SBP (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">122.16±12.45 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">142.73±17.56<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">*</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">165.08±19.61<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">##</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">DBP (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">78.29±8.45 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">85.94±14.08<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">*</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">91.83±15.34<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">*</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">#</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Pulse pressure (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">44.88±7.98 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">57.07±9.90<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">74.30±10.85<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">##</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Cystatin C \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.78±0.23 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.07±0.37<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.34±0.58<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">**</span></a><span class="elsevierStyleSup">,</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">##</span></a> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab580103.png" ] ] ] "notaPie" => array:4 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "*" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">p<0.05.</p>" ] 1 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "**" "nota" => "<p class="elsevierStyleNotepara" id="npar0010">p<0.01.</p> <p class="elsevierStyleNotepara" id="npar0015">Compared with MetD group:</p>" ] 2 => array:3 [ "identificador" => "tblfn0015" "etiqueta" => "#" "nota" => "<p class="elsevierStyleNotepara" id="npar0020">p<0.05.</p>" ] 3 => array:3 [ "identificador" => "tblfn0020" "etiqueta" => "##" "nota" => "<p class="elsevierStyleNotepara" id="npar0025">p<0.01.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Comparison of baseline data between MetS, MetD and control groups (x¯±s).</p>" ] ] 2 => array:7 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:2 [ "leyenda" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">BMI: body mass index; DBP: diastolic blood pressure; FPG: fasting plasma glucose; HbA1c: hemoglobin A1c; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; SBP: systolic blood pressure; TG: triglycerides; WC: waist circumference.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Variable \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">r</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t</td></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">BMI \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.487 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.007 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Waist–hip ratio \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.364 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.002 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">WC \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.520 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.015 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Waist–height ratio \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.562 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.000 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LDL-C \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.203 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.058 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HDL-C \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.219 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.046 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">TG \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.285 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.040 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">FPG \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.442 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.000 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HBA1c \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.371 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.045 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SBP \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.464 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.004 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">DBP \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.322 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.029 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">pulse pressure \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.376 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.006 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab580102.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Correlation of cystatin C and other variables.</p>" ] ] 3 => array:7 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:2 [ "leyenda" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">FPG: fasting plasma glucose; SBP: systolic blood pressure; SE: standard error; TG: triglycerides.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Variable \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">β \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">SE \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Wald chi-square \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Exp(B) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">95% CI \t\t\t\t\t\t\n \t\t\t\t</td></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Waist–height ratio \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.695 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.720 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.617 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.406 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.965–15.098 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Waist circumference \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.590 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.607 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8.941 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.008 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.951 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.351–9.270 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Cystatin C \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.239 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.445 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.756 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.164 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.136–8.259 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SBP \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.511 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.489 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9.035 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.047 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.105 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.218–9.772 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">FPG \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.633 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.202 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9.800 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.012 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.883 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.267–2.799 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Pulse pressure \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.942 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.192 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8.439 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.747 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.198–2.545 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">TG \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.313 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.097 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.238 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.004 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.526 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.111–0.515 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab580101.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Multivariate logistic regression analysis of predictors for metabolic syndrome.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:21 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ 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| Ano/Mês | Html | Total | |
|---|---|---|---|
| 2024 Novembro | 11 | 5 | 16 |
| 2024 Outubro | 47 | 28 | 75 |
| 2024 Setembro | 39 | 26 | 65 |
| 2024 Agosto | 34 | 32 | 66 |
| 2024 Julho | 38 | 36 | 74 |
| 2024 Junho | 41 | 25 | 66 |
| 2024 Maio | 50 | 15 | 65 |
| 2024 Abril | 47 | 26 | 73 |
| 2024 Maro | 48 | 24 | 72 |
| 2024 Fevereiro | 43 | 30 | 73 |
| 2024 Janeiro | 30 | 35 | 65 |
| 2023 Dezembro | 32 | 35 | 67 |
| 2023 Novembro | 44 | 19 | 63 |
| 2023 Outubro | 20 | 15 | 35 |
| 2023 Setembro | 38 | 18 | 56 |
| 2023 Agosto | 37 | 19 | 56 |
| 2023 Julho | 26 | 11 | 37 |
| 2023 Junho | 27 | 8 | 35 |
| 2023 Maio | 47 | 32 | 79 |
| 2023 Abril | 34 | 5 | 39 |
| 2023 Maro | 40 | 23 | 63 |
| 2023 Fevereiro | 24 | 18 | 42 |
| 2023 Janeiro | 17 | 15 | 32 |
| 2022 Dezembro | 31 | 23 | 54 |
| 2022 Novembro | 53 | 22 | 75 |
| 2022 Outubro | 35 | 17 | 52 |
| 2022 Setembro | 27 | 31 | 58 |
| 2022 Agosto | 35 | 41 | 76 |
| 2022 Julho | 41 | 40 | 81 |
| 2022 Junho | 26 | 18 | 44 |
| 2022 Maio | 28 | 35 | 63 |
| 2022 Abril | 32 | 30 | 62 |
| 2022 Maro | 28 | 40 | 68 |
| 2022 Fevereiro | 32 | 24 | 56 |
| 2022 Janeiro | 31 | 24 | 55 |
| 2021 Dezembro | 24 | 35 | 59 |
| 2021 Novembro | 31 | 33 | 64 |
| 2021 Outubro | 35 | 41 | 76 |
| 2021 Setembro | 29 | 29 | 58 |
| 2021 Agosto | 25 | 36 | 61 |
| 2021 Julho | 42 | 37 | 79 |
| 2021 Junho | 30 | 26 | 56 |
| 2021 Maio | 46 | 25 | 71 |
| 2021 Abril | 38 | 50 | 88 |
| 2021 Maro | 67 | 17 | 84 |
| 2021 Fevereiro | 85 | 18 | 103 |
| 2021 Janeiro | 35 | 12 | 47 |
| 2020 Dezembro | 32 | 4 | 36 |
| 2020 Novembro | 34 | 23 | 57 |
| 2020 Outubro | 29 | 10 | 39 |
| 2020 Setembro | 90 | 14 | 104 |
| 2020 Agosto | 34 | 8 | 42 |
| 2020 Julho | 33 | 7 | 40 |
| 2020 Junho | 55 | 4 | 59 |
| 2020 Maio | 58 | 6 | 64 |
| 2020 Abril | 34 | 16 | 50 |
| 2020 Maro | 49 | 7 | 56 |
| 2020 Fevereiro | 45 | 14 | 59 |
| 2020 Janeiro | 53 | 4 | 57 |
| 2019 Dezembro | 29 | 7 | 36 |
| 2019 Novembro | 27 | 3 | 30 |
| 2019 Outubro | 45 | 2 | 47 |
| 2019 Setembro | 15 | 8 | 23 |
| 2019 Agosto | 57 | 4 | 61 |
| 2019 Julho | 37 | 13 | 50 |
| 2019 Junho | 26 | 3 | 29 |
| 2019 Maio | 52 | 12 | 64 |
| 2019 Abril | 26 | 14 | 40 |
| 2019 Maro | 42 | 11 | 53 |
| 2019 Fevereiro | 63 | 10 | 73 |
| 2019 Janeiro | 40 | 9 | 49 |
| 2018 Dezembro | 55 | 11 | 66 |
| 2018 Novembro | 147 | 12 | 159 |
| 2018 Outubro | 407 | 26 | 433 |
| 2018 Setembro | 57 | 10 | 67 |
| 2018 Agosto | 90 | 14 | 104 |
| 2018 Julho | 31 | 6 | 37 |
| 2018 Junho | 46 | 6 | 52 |
| 2018 Maio | 42 | 8 | 50 |
| 2018 Abril | 38 | 2 | 40 |
| 2018 Maro | 57 | 14 | 71 |
| 2018 Fevereiro | 33 | 5 | 38 |
| 2018 Janeiro | 33 | 13 | 46 |
| 2017 Dezembro | 64 | 18 | 82 |
| 2017 Novembro | 42 | 25 | 67 |
| 2017 Outubro | 46 | 7 | 53 |
| 2017 Setembro | 64 | 10 | 74 |
| 2017 Agosto | 46 | 21 | 67 |
| 2017 Julho | 24 | 7 | 31 |
| 2017 Junho | 51 | 12 | 63 |
| 2017 Maio | 32 | 8 | 40 |
| 2017 Abril | 19 | 5 | 24 |
| 2017 Maro | 28 | 7 | 35 |
| 2017 Fevereiro | 28 | 3 | 31 |
| 2017 Janeiro | 20 | 4 | 24 |
| 2016 Dezembro | 27 | 7 | 34 |
| 2016 Novembro | 13 | 7 | 20 |
| 2016 Outubro | 29 | 8 | 37 |
| 2016 Setembro | 15 | 5 | 20 |
| 2016 Agosto | 9 | 3 | 12 |
| 2016 Julho | 9 | 5 | 14 |
| 2016 Junho | 20 | 6 | 26 |
| 2016 Maio | 6 | 4 | 10 |
| 2016 Abril | 30 | 6 | 36 |
| 2016 Maro | 43 | 7 | 50 |
| 2016 Fevereiro | 43 | 24 | 67 |
| 2016 Janeiro | 47 | 21 | 68 |
| 2015 Dezembro | 52 | 11 | 63 |
| 2015 Novembro | 36 | 16 | 52 |
| 2015 Outubro | 37 | 15 | 52 |
| 2015 Setembro | 45 | 14 | 59 |
| 2015 Agosto | 48 | 14 | 62 |
| 2015 Julho | 27 | 3 | 30 |
| 2015 Junho | 36 | 8 | 44 |
| 2015 Maio | 61 | 16 | 77 |
| 2015 Abril | 39 | 6 | 45 |
| 2015 Maro | 40 | 17 | 57 |
| 2015 Fevereiro | 31 | 9 | 40 |
| 2015 Janeiro | 24 | 20 | 44 |
| 2014 Dezembro | 43 | 13 | 56 |
| 2014 Novembro | 50 | 25 | 75 |
| 2014 Outubro | 55 | 29 | 84 |
| 2014 Setembro | 95 | 54 | 149 |
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