Relationship between lipoprotein (a) and subclinical carotid atherosclerosis in asymptomatic individuals

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Dias, Maira C. Ferreira, Expedito J.A. Luna" "autores" => array:4 [ 0 => array:2 [ "nombre" => "Caio Medeiros" "apellidos" => "Fernandes" ] 1 => array:2 [ "nombre" => "Shirley L." "apellidos" => "Dias" ] 2 => array:2 [ "nombre" => "Maira C." "apellidos" => "Ferreira" ] 3 => array:2 [ "nombre" => "Expedito J.A." "apellidos" => "Luna" ] ] ] ] "resumen" => array:1 [ 0 => array:3 [ "titulo" => "Highlights" "clase" => "author-highlights" "resumen" => "<ul class="elsevierStyleList" id="celist0001"><li class="elsevierStyleListItem" id="celistitem0001">•Vaccination with any vaccine was effective in preventing confirmed COVID-19 cases.</li><li class="elsevierStyleListItem" id="celistitem0002">•CoronaVac was effective in preventing COVID-19 related hospitalizations.</li><li class="elsevierStyleListItem" id="celistitem0003">•Vaccination had a significant impact in reducing cases and hospitalizations.</li><li class="elsevierStyleListItem" id="celistitem0004">•Predominance of mild cases, with respiratory symptoms, myalgia, and headache.</li><li class="elsevierStyleListItem" id="celistitem0005">•Vaccine protection waned over time.</li></ul>" ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S1807593222033105?idApp=UINPBA00004N" "url" => 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[ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0002" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1210 "Ancho" => 2500 "Tamanyo" => 105813 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0004" "detalle" => "Fig " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Subgroup analysis for the association between VAI and severe AAC." ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Zheng Qin, Luojia Jiang, Jiantong Sun, Jiwen Geng, Shanshan Chen, Qinbo Yang, Baihai Su, Ruoxi Liao" "autores" => array:8 [ 0 => array:2 [ "nombre" => "Zheng" "apellidos" => "Qin" ] 1 => array:2 [ "nombre" => "Luojia" "apellidos" => "Jiang" ] 2 => array:2 [ "nombre" => "Jiantong" "apellidos" => "Sun" ] 3 => array:2 [ "nombre" => "Jiwen" "apellidos" => "Geng" ] 4 => array:2 [ "nombre" => "Shanshan" "apellidos" => "Chen" ] 5 => array:2 [ "nombre" => "Qinbo" "apellidos" => "Yang" ] 6 => array:2 [ "nombre" => "Baihai" "apellidos" => "Su" ] 7 => array:2 [ "nombre" => "Ruoxi" "apellidos" => "Liao" ] ] ] ] "resumen" => array:1 [ 0 => array:3 [ "titulo" => "Highlights" "clase" => "author-highlights" "resumen" => "<ul class="elsevierStyleList" id="celist0001"><li class="elsevierStyleListItem" id="celistitem0001">•Higher Adiposity Index (VAI) tertile shows higher rates of Abdominal Aortic Calcification (AAC).</li><li class="elsevierStyleListItem" id="celistitem0002">•Each unit increase in VAI was associated with 4% higher likelihood of severe AAC.</li><li class="elsevierStyleListItem" id="celistitem0003">•Increased visceral adiposity evaluating by VAI associated with a higher AAC score.</li><li class="elsevierStyleListItem" id="celistitem0004">•This positive relationship was more significant in normal weight population.</li></ul>" ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S1807593222033154?idApp=UINPBA00004N" "url" => "/18075932/000000770000000C/v3_202308251443/S1807593222033154/v3_202308251443/en/main.assets" ] "en" => array:18 [ "idiomaDefecto" => true "cabecera" => "Original articles" "titulo" => "Relationship between lipoprotein (a) and subclinical carotid atherosclerosis in asymptomatic individuals" "tieneTextoCompleto" => true "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Victor França, Érica Ivana Lázaro Gomes, Edite Vieira Silva de Campos, Vanessa Helena de Souza Zago, Valéria Sutti Nunes, Eliana Cotta de Faria" "autores" => array:6 [ 0 => array:4 [ "nombre" => "Victor" "apellidos" => "França" "email" => array:1 [ 0 => "victtor_franca@hotmail.com" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0001" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0001" ] ] ] 1 => array:3 [ "nombre" => "Érica Ivana Lázaro" "apellidos" => "Gomes" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0001" ] ] ] 2 => array:3 [ "nombre" => "Edite Vieira Silva" "apellidos" => "de Campos" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0001" ] ] ] 3 => array:3 [ "nombre" => "Vanessa Helena de Souza" "apellidos" => "Zago" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0002" ] ] ] 4 => array:3 [ "nombre" => "Valéria Sutti" "apellidos" => "Nunes" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "c" "identificador" => "aff0003" ] ] ] 5 => array:3 [ "nombre" => "Eliana Cotta" "apellidos" => "de Faria" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0001" ] ] ] ] "afiliaciones" => array:3 [ 0 => array:3 [ "entidad" => "Department of Clinical Pathology, Faculdade de Ciências Médicas da Universidade Estadual de Campinas, Campinas, SP, Brazil" "etiqueta" => "a" "identificador" => "aff0001" ] 1 => array:3 [ "entidad" => "Pontifical Catholic University of Campinas, São Paulo, Brazil" "etiqueta" => "b" "identificador" => "aff0002" ] 2 => array:3 [ "entidad" => "Laboratorio de Lipides (LIM10), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, BR" "etiqueta" => "c" "identificador" => "aff0003" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0001" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "textoCompleto" => "IntroductionLipoprotein (a) ‒ Lp(a) is a lipoprotein fraction similar to the Low-Density Lipoprotein (LDL), that contains an apolipoprotein (a) linked to its structure. Plasma levels of Lp(a) display a wide range in the general population and is primarily controlled by hepatic synthesis of apo (a), which in turn varies according to the presence of polymorphisms in the LPA gene.<a class="elsevierStyleCrossRef" href="#bib0001">1</a> Despite the similarities with plasminogen structure, apolipoprotein (a) contains only the Kringle (K) IV and V in its structure. Among the subtypes of KIV, specifically, subtype two of KIV (KIV2) presents a variable number of copies, reaching more than 40, thus it is possible to reach up to 34 different apo (a) isoforms.<a class="elsevierStyleCrossRef" href="#bib0002">2</a>,<a class="elsevierStyleCrossRef" href="#bib0003">3</a>Levels of Lp(a) are considered an independent risk factor for cardiovascular disease according to epidemiologic and genetic studies carried out in different populations. In spite of it, reference risk values are not usually adopted.<a class="elsevierStyleCrossRef" href="#bib0001">1</a>,<a class="elsevierStyleCrossRef" href="#bib0004">4</a>,<a class="elsevierStyleCrossRef" href="#bib0005">5</a>Lp(a) levels remain relatively constant in an individual throughout life and are not significantly affected by diet, age, and physical activity.<a class="elsevierStyleCrossRef" href="#bib0006">6</a> Still, they vary according to ethnicity: individuals of African American descent have two to three times higher concentrations compared to Caucasians<a class="elsevierStyleCrossRef" href="#bib0007">7</a> although Lp(a) levels may have a greater influence on plaque burden in white than in black individuals.<a class="elsevierStyleCrossRef" href="#bib0008">8</a>The association of Lp(a) and cardiovascular diseases is justified by the atherogenic risk attached to the LDL structure and is aggravated by the similarity of apo (a) structure to plasminogen that could interfere in hemostasis. This effect may explain the role of Lp(a) in the promotion of cardiovascular diseases, eventually favoring atherogenic and prothrombotic processes.<a class="elsevierStyleCrossRef" href="#bib0001">1</a>,<a class="elsevierStyleCrossRef" href="#bib0009">9</a>There is evidence that high Lp(a) levels, especially above 30 mg/dL, contribute to the progression of atherosclerotic plaque and increased carotid Intima-Media Thickness (cIMT).<a class="elsevierStyleCrossRefs" href="#bib0010">10–13</a> However, this issue remains under debate. While some studies associate Lp(a) independently with cIMT and plaque development, other studies have not shown such an association.<a class="elsevierStyleCrossRefs" href="#bib0014">14–18</a> Furthermore, given the important role of Lp(a) in the development of cardiovascular diseases, the present study aimed to explore the association between Lp(a) levels and subclinical carotid atherosclerosis measured as cIMT as well as the presence of carotid plaques in asymptomatic individuals.Materials and methodsStudy populationThis is a cross-section, retrospective study, for which were selected 317 individuals from both genders, aged between 19 and 77 years old, between the years 2008 and 2013, who participated in the FAPESP Thematic Project 2006/60585-9, after authorization by the Research Ethics Committee of the Faculty of Medical Sciences/UNICAMP. The study was carried out in accordance with the Declaration of Helsinki.This project was carried out in partnership with the Municipal Health Department of Campinas, which provided the laboratory results of the lipid profile of individuals who spontaneously sought healthcare in the Basic Health Units of the city of Campinas, São Paulo, Brazil. As previously reported by Parra et al.<a class="elsevierStyleCrossRef" href="#bib0019">19</a> the volunteers were initially selected according to plasma LDL-C (≤ 130 mg/dL) and triglycerides (≤ 150 mg/dL) levels. Thus, they were contacted by telephone and answered a screening questionnaire regarding medication use, Body Mass Index (BMI), and current and pre-existing diseases. The individuals who met the inclusion criteria were invited to attend clinical and laboratory evaluations.On admission, all volunteers signed the Informed Consent Form (ICF) before a complete clinical, anthropometric, and laboratory evaluation. Peripheral venous blood samples were drawn in EDTA-containing tubes after a 12-hour fasting period. Serum and plasma were separated by centrifugation (4°C, 1000g, 10 minutes) and stored at -80°C until further analysis.The inclusion criteria were both genders, BMI between 20 and 30 kg/m2; LDL-C ≤ 130 mg/dL and triglycerides ≤ 150 mg/dL levels, Systolic Blood Pressure (SBP) ≤ 140 mmHg or Diastolic Blood Pressure (DBP) ≤ 90 mmHg. Exclusion criteria comprised BMI higher than 30 kg/m2, regular use of medical treatment, especially those which interfere with lipids metabolism (statins, fibrates, oral contraceptives, and hormonal replacement therapy), and clinical and/or laboratory evidence of thyroid dysfunction, dyslipidemia, diabetes, metabolic syndrome, pregnancy, hypertension, liver, kidney or pulmonary disease, alcoholism, and smoking. Individuals who attend the inclusion criteria were invited to undergo carotid ultrasonography in a second visit.Clinical and anthropometrical evaluationVolunteers answered a detailed questionnaire regarding their medical history, and their race was self-reported as white, black, or mixed.Determinations included systolic and diastolic blood pressure (SBP and DBP, respectively) body weight (kg), height (cm), and circumferences of the waist and hips (WC, cm). Thus, BMI, waist-to-hip and waist-to-height ratios, all considered adiposity markers were calculated.<a class="elsevierStyleCrossRef" href="#bib0020">20</a> The Lipid Accumulation Product (LAP) was also calculated according to the waist circumference and triglycerides levels (mmoL/dL) as described previously.<a class="elsevierStyleCrossRef" href="#bib0021">21</a>Biochemical analysisTotal Cholesterol (TC), High-Density Lipoprotein Cholesterol (HDL-C), triglycerides, glucose, uric acid, urea, alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transferase, creatinine and alkaline phosphatase were determined in the automatized system Modular® Analytics Evo (Roche Diagnostics, Burgess Hill, West Sussex, UK) using commercially available Roche Diagnostics® (Mannheim, Germany) assays. Thyroid Stimulation Hormone (TSH) and Thyroxin (T4L) were also determined in the automated system Elecsys 2010 (Roche, Basel, Switzerland) using Roche Diagnostics® (Mannheim, Germany) assays.Low-Density Lipoprotein Cholesterol (LDL-C), and Very-Low Density Lipoprotein Cholesterol (VLDL-C) were determined by Friedewald's equation, and by triglycerides/5, respectively,<a class="elsevierStyleCrossRef" href="#bib0022">22</a> Non-HDL Cholesterol (NHDL-C) were calculated by subtracting the HDL-C levels from total cholesterol.Apolipoproteins A-I (apo A-I), B-100 (apo B-100) and [Lp(a)] were determined by nephelometry in the automated system BN II (Siemens Healthcare Diagnostics, Marburg, Germany) using commercially available assays (Dade-Boehringer®, Deerfield, IL, USA). C-Reactive Protein (CRP) was measured by immunoturbidimetry using the Tina-quant® CRP (latex) high-sensitivity assay (Roche Diagnostics®, Mannheim, Germany).Plasma Paraoxonase-1 activity (PON1) was evaluated through an enzymatic method using paraoxon (diethyl-p-nitrophenylphosphate, Sigma, St. Louis, MO) as substrate.<a class="elsevierStyleCrossRef" href="#bib0023">23</a>Carotid Intima-Media Thickness (cIMT) determination and carotid plaques detectionThe determinations of cIMT and plaques were performed by a single trained radiologist, blind to the study participants. Determinations were made by high-resolution B-mode ultrasonography using a 6–9 MHz linear array ultrasound imaging system ATL HDI 3500 Ultrasound System (Advanced Technology Laboratories Ultrasound, Bothell, USA). The volunteers were examined in dorsal decubitus and five longitudinal measurements of segments of left, and right common carotid arteries at the distal wall and 1 cm from the bifurcation were performed. Mean cIMT (mm) was calculated as the average of these measurements, and cIMT below 0.90 mm was considered a normal reference.<a class="elsevierStyleCrossRef" href="#bib0024">24</a> In addition, it was considered as plaque the presence of at least one of the following parameters: focal wall thickening with at least 0.5 mm toward the vessel lumen, focal wall thickening at least 50% greater than that of the surrounding vessel wall, or focal region with cIMT above 1.5 mm that protrudes into the lumen that is distinct from the adjacent boundary.<a class="elsevierStyleCrossRef" href="#bib0025">25</a>,<a class="elsevierStyleCrossRef" href="#bib0026">26</a>Statistical analysisThe statistical analyses were performed using the software SAS 9.2 (SAS Institute Inc., Cary, NC, USA) and the SPSS 16.0 (SPSS Inc. Released 2007. SPSS for Windows, Version 16.0. Chicago, SPSS Inc.). A two-sided p-value ≤ 0.05 was considered statistically significant, and p-values > 0.05 and < 0.08 were determined as borderline.Data normality was verified by the Shapiro-Wilk test. Due to the absence of normal distribution, numeric data were expressed as median and interquartile ranges and were adopted non-parametric tests. In order to explore the relationship between Lp(a) and the studied variables, the Spearman correlation test was performed. In addition, the parameters were compared by the Mann-Whitney test according to Lp(a) levels (≤ 30 mg/dL and > 30 mg/dL).Univariate and multivariate linear regression analyses were performed to evaluate the influence of Lp(a) levels on the other studied parameters. Numeric variables were transformed into ranks due to the absence of normal distribution, and the results were as coefficients of determination (partial R2 and R2). Logistic regression analysis was performed in order to determine the Odds Ratio (OR) for plaque presence in the studied population.Results<a class="elsevierStyleCrossRef" href="#tbl0001">Table 1</a> presents the descriptive analysis for clinical, anthropometrical, and biochemical parameters. The total population (n = 317; 51% female) was asymptomatic, with normal weight, blood pressure, and plasma lipids, in accordance with the respective guidelines adopted.<a class="elsevierStyleCrossRef" href="#bib0020">20</a>,<a class="elsevierStyleCrossRefs" href="#bib0027">27–29</a> Among the volunteers, 23% present increased cIMT (≥0.90 mm), and 18% were identified with carotid plaques.<elsevierMultimedia ident="tbl0001"></elsevierMultimedia>The variables were compared between groups stratified according to Lp(a) levels (<a class="elsevierStyleCrossRef" href="#tbl0002">Table 2</a>). The group with levels above 30 mg/Dl (21%) exhibited a higher median age, apolipoprotein B-100, PON1 activity, and GGT levels. In addition, the presence of plaques and non-white individuals was also significantly more frequent in this group.<elsevierMultimedia ident="tbl0002"></elsevierMultimedia>Spearman's correlation between Lp(a) and the other parameters revealed positive and significant correlations with age (R = 0.167; p < 0.01), SBP (R = 0.136; p < 0.02), DBP (R = 0.109; p = 0.05), ApoB-100 (R = 0.258; p < 0.01), PON1 (R = 0.108; p = 0.05), GGT (R = 0.123; p = 0.03), hsCRP (R = 0.157; p < 0.01), and a tendency towards cIMT (R = 0.099; p = 0.08).The possible associations between Lp(a) and the other variables were explored in the analysis of univariate and multivariate linear regression, whose significant parameters are shown in <a class="elsevierStyleCrossRef" href="#tbl0003">Table 3</a>. Direct and significant associations with age and race were observed, both in the univariate and multivariate analyses. SBP and DBP are also directly associated with Lp(a) in univariate analysis, however, they did not show significance in multivariate analysis. The LAP, an adiposity parameter, was indirectly related to Lp(a) in both univariate and multivariate analyses.<elsevierMultimedia ident="tbl0003"></elsevierMultimedia><a class="elsevierStyleCrossRef" href="#tbl0004">Table 4</a> shows the analysis of univariate and multivariate logistic regression to explore the association between the presence of plaques, Lp(a), and other parameters. With each year of life, the odds ratio for plaque increases by about 1.11 times (11%). For non-white individuals, the odds ratio for the plaque is approximately 1.97 times (97%) in univariate, and 2.5 times (250%) in the multivariate analysis. Regarding Lp(a) concentrations above 30 mg/dL, there is a 2% increase in the odds ratio for plaque in univariate analysis.<elsevierMultimedia ident="tbl0004"></elsevierMultimedia>DiscussionThe present study investigated the possible relationships between plasma Lp(a) levels and subclinical atherosclerosis determined by cIMT, as well as the presence of carotid plaques in asymptomatic adults. The group selected for this study consisted of individuals of both genders, predominantly self-declared as white (82%) and clinically assessed as normotensive, normolipidemic, and eutrophic, with no evidence of pre-established cardiovascular diseases or other pathologies. In addition, the group consists of adults (with a median age of 43 years), of whom carotid plaques were reported in 18%.The contribution of cIMT to the prediction of cardiovascular risk is widely reported in the literature, and the presence of plaques adds significant value to this determination illustrating the heterogeneity of the atherosclerotic disease. On the one hand, the cIMT reflects the thickening process of the intima-medial layer that normally increases with age and smooth muscle hypertrophy. In contrast, the presence of plaques is specific and shows the established atherosclerotic disease.<a class="elsevierStyleCrossRef" href="#bib0030">30</a>The occurrence of carotid atherosclerotic plaques is recognized to increase with age, however, the prevalence in populations can vary significantly according to the methods applied for its determination and the definition of plaque adopted. Another sensitive point is the population itself, concerning the presence of comorbidities, lifestyle, and type of diet, among other factors. For example, Ihle-Hansen and colleagues<a class="elsevierStyleCrossRef" href="#bib0031">31</a> evaluated cIMT and the presence of plaques in 3683 individuals aged between 63 and 65 years; in this group, 87% had carotid plaques. Not surprisingly, the presence of risk factors was significant, of which hypertension (62%), hypercholesterolemia (53%), obesity (23%), and diabetes mellitus (11%) stand out. In this sense, age plus the presence of these other well-established risk factors explain this high plaque prevalence. Other studies in the general population corroborate the high prevalence of atherosclerotic plaques according to the age group and the presence of other risk factors, whose severity increases significantly as these clinical aspects add up.<a class="elsevierStyleCrossRef" href="#bib0032">32</a> Recently, Song P. and collaborators evaluated from a robust meta-analysis that the prevalence of atherosclerotic plaques in the population between 30 and 79 years is 21.13%, which is equivalent to more than 800 million people.<a class="elsevierStyleCrossRef" href="#bib0033">33</a>Studies assessing the cIMT and the prevalence of plaques in asymptomatic individuals and their association with non-established risk factors such as Lp(a) are scarce. A study with 6617 Chinese, with no history of CVD, diabetes mellitus, hypertension, and smoking found a mean cIMT of 0.60 mm, considering their age was 49.7 ± 5.3.<a class="elsevierStyleCrossRef" href="#bib0034">34</a> Regarding plaques, the prevalence was 9%, lower than that observed in the present study. This finding, on the one hand, points to the possibility of the presence of an underlying factor, hypothetically Lp(a), which, apart from traditional factors, may contribute to this relatively high prevalence. On the other hand, it shows the challenge in interpreting parameters that vary according to the technique used, location and number of measurements, number of individuals enrolled, and software algorithm analysis. In this sense, it is possible to state that cIMT and plaques are unlikely to be directly compared, even among groups of healthy individuals.As expected, age was a factor strongly associated with carotid plaques in this study, although it was composed of healthy individuals. However, the association between Lp(a) levels higher than 30 mg/dL, and the odds ratio for plaques in the univariate analysis suggests a relationship that can be explored. Tsimikas and colleagues (1) reported the presence of apo (a) in atherosclerotic plaques, suggesting that Lp(a) in high concentrations may contribute to plaque progression. There was a positive association between Lp(a) and carotid atherosclerosis in adults with ischemic stroke aged 16 to 54 years in France.<a class="elsevierStyleCrossRef" href="#bib0012">12</a> The Lp(a) has also been associated with the development of atherosclerosis in individuals with primary hypercholesterolemia and Lp(a) concentrations greater than 50 mg/dL in a group of individuals aged 18 to 80 years in Spain.<a class="elsevierStyleCrossRef" href="#bib0035">35</a> Hippe and colleagues<a class="elsevierStyleCrossRef" href="#bib0013">13</a> reported that Lp(a) concentrations greater than 64 mg/dL were independent predictors of carotid plaque progression in individuals with established cardiovascular disease, even maintaining serum LDL-C concentrations below 70 mg/dL. However, Huffman and colleagues<a class="elsevierStyleCrossRef" href="#bib0018">18</a> did not find an association between Lp(a) concentrations and atherosclerosis among South Asians living in America aged 40 to 84 years without cardiovascular disease. Some studies independently associate Lp(a) with cIMT and carotid atherosclerotic plaques, other studies, however, do not show this correlation, and others in turn report that Lp(a) is more associated with established CVD than in asymptomatic individuals, once that Lp(a) concentrations tend to increase in chronic inflammatory processes, such as rheumatoid arthritis and systemic lupus erythematosus.<a class="elsevierStyleCrossRef" href="#bib0002">2</a>,<a class="elsevierStyleCrossRef" href="#bib0003">3</a>,<a class="elsevierStyleCrossRef" href="#bib0014">14</a>In this study, no correlation was found between Lp(a) and cIMT. Nonetheless, Knoflach and collaborators<a class="elsevierStyleCrossRef" href="#bib0036">36</a> found a direct association between Lp(a) and cIMT in asymptomatic Austrian women aged 18 to 22 similarly to the study by Schreiner and collaborators<a class="elsevierStyleCrossRef" href="#bib0037">37</a> that found a positive correlation between Lp(a) and cIMT in Americans aged 45 to 64, suggesting that Lp(a) may be associated with development subclinical carotid atherosclerosis. However, Calmarza and colleagues<a class="elsevierStyleCrossRef" href="#bib0016">16</a> did not find such an association in a study of 172 asymptomatic Spanish individuals aged 43 to 93 years. This association is, in fact, a sensitive point for analysis, since the increase in cIMT can be associated with carotid plaque, however, cIMT cannot be considered an independent predictor of the development of carotid plaque, although these events often coexist and share some vascular determinants common.<a class="elsevierStyleCrossRef" href="#bib0038">38</a>It is agreed that the plasma concentrations of Lp(a) are genetically determined more specifically by the presence of polymorphisms in the LPA gene that determine the size of the type 2 kringle IV peptide chain (KIV-2) (3). Thus, the larger the size of KIV-2, the greater the Lp(a); in contrast, its plasma concentration is lower. This reverse process is associated with the easier removal of larger particles, while smaller ones tend to remain in circulation for longer periods.<a class="elsevierStyleCrossRef" href="#bib0009">9</a> Evidence points to the participation of LDLR in the removal process, including as a therapeutic target for reducing plasma Lp(a) concentrations. Nonetheless, many contradictions regarding the results observed with statins and PCSK9 inhibitors must be considered.<a class="elsevierStyleCrossRef" href="#bib0001">1</a>,<a class="elsevierStyleCrossRef" href="#bib0003">3</a>Given the complexity of this lipoprotein, reference values have not been defined for the general population. In fact, studies in different ethnic and population groups point to a wide range. Thus, some studies indicate that values above 50 mg/dL (125 nmoL/L) or the 80th percentile are considered high.<a class="elsevierStyleCrossRef" href="#bib0009">9</a> Other studies, on the other hand, adopt the 30 mg/dL cut.<a class="elsevierStyleCrossRef" href="#bib0001">1</a>,<a class="elsevierStyleCrossRef" href="#bib0008">8</a>,<a class="elsevierStyleCrossRef" href="#bib0009">9</a>,<a class="elsevierStyleCrossRefs" href="#bib0039">39–42</a> In fact, 21% of the recruited individuals had Lp(a) above this value. Some studies show that around 30% of the world population has high Lp(a), which represents approximately two billion individuals.<a class="elsevierStyleCrossRef" href="#bib0001">1</a>,<a class="elsevierStyleCrossRef" href="#bib0009">9</a>,<a class="elsevierStyleCrossRef" href="#bib0018">18</a> The Lp(a) concentrations in the asymptomatic individuals of the present study were expressed with a median of 12 mg/dL (4‒26th percentiles), indicating great similarity with other studies.<a class="elsevierStyleCrossRef" href="#bib0043">43</a> In a study with Brazilian individuals aged 46 to 68 years, to verify a possible association between concentrations of Lp(a) and coronary artery disease, the control group showed average concentrations of 11 mg/dL of Lp(a).<a class="elsevierStyleCrossRef" href="#bib0044">44</a> Another study carried out in the city of Ouro Preto, state of Minas Gerais, Brazil, with 400 asymptomatic individuals, showed Lp(a) concentrations with a median of 18.11 mg/dL with an average age of 45 years.<a class="elsevierStyleCrossRef" href="#bib0045">45</a> Schoolchildren averaging 10 years-old, also demonstrated Lp(a) concentrations with a median of 25.5 mg/dL in the Ouro Preto study.<a class="elsevierStyleCrossRef" href="#bib0045">45</a> A recent study involving 4,140 individuals in a cardiovascular reference center in São Paulo, showed an average Lp(a) concentration of 24.8 mg/dL.<a class="elsevierStyleCrossRef" href="#bib0046">46</a>In addition, interesting relationships were observed in this study between Lp(a) levels and race. Several shreds of evidence in the literature point to those non-white individuals having higher concentrations of Lp(a), about two to three times higher than Caucasians or Orientals, revealing that there is ethnic variability between different population groups, whose underlying causes have not yet been fully understood.<a class="elsevierStyleCrossRef" href="#bib0003">3</a>,<a class="elsevierStyleCrossRef" href="#bib0047">47</a>It was possible to perceive in the present study that serum Lp(a) concentrations in non-white individuals were higher, with a median of 22.85 mg/dL (5‒36 percentiles), and in white individuals with a median of 11.10 mg/dL (4‒22 percentiles), with the significance level of p < 0.01 when compared by the Mann-Whitney test. These concentrations can be partially explained by variations in the LPA locus, mainly by the polymorphism of the apo (a) gene (LPA; MIM 152200). Among the variants, notably Schmidt and colleagues evaluated three SNPs and reported that they contribute to different concentrations of Lp(a) in African-American and Caucasian individuals.<a class="elsevierStyleCrossRef" href="#bib0047">47</a> Two SNPs (T3888P and G + 1/inKIV-8A), suppressing the Lp(a) set, were more common in Caucasians, while the third SNP (G-21A) increased the activity of promoting apo (a), this being more common in African Americans.<a class="elsevierStyleCrossRef" href="#bib0003">3</a>Other studies looked at different populations and found low concentrations also in non-Hispanic Caucasians with a median of 12 mg/dL (5‒32 percentiles), in Chinese with a median of 11 mg/dL (5‒26 percentiles), in Japanese with a median of 13 mg/dL (5‒26 percentiles), and in Hispanics with a median of 19 mg/dL (8‒43 percentiles).<a class="elsevierStyleCrossRef" href="#bib0001">1</a>,<a class="elsevierStyleCrossRef" href="#bib0003">3</a>,<a class="elsevierStyleCrossRef" href="#bib0009">9</a>,<a class="elsevierStyleCrossRef" href="#bib0047">47</a> Even with different concentrations and isoforms in some populations, Lp(a) was associated positively and similarly with the risk of cardiovascular events in a 20-year longitudinal follow-up study among Caucasian individuals and individuals of African descent.<a class="elsevierStyleCrossRef" href="#bib0001">1</a> Given this, there is still a lot of discussion about the concentrations considered adequate for Lp(a) due to the great miscegenation of the population, mainly in countries like Brazil.<a class="elsevierStyleCrossRef" href="#bib0006">6</a>Other factors such as age, sex, and environmental conditions do not have a major influence on Lp(a) concentrations in most studies. However, in the present study, Lp(a) concentrations greater than 30 mg/dL were found in older individuals. Some studies suggest that among adults, Lp(a) concentrations have been somewhat variable, and an association between Lp(a) and longevity has been suggested among the elderly.<a class="elsevierStyleCrossRefs" href="#bib0048">48–50</a> On the other hand, a substantial number of studies report that there is not an association between age and Lp(a) concentrations, however, the question of the extent to which age can influence Lp(a) concentrations remains uncertain.<a class="elsevierStyleCrossRef" href="#bib0006">6</a>,<a class="elsevierStyleCrossRef" href="#bib0049">49</a>In the present study, there was no significant difference between the concentrations of Lp(a) and gender. However, a meta-analysis with 36 studies showed that females had 12% higher concentrations of Lp(a) compared to males.<a class="elsevierStyleCrossRef" href="#bib0051">51</a> Likewise, it occurred with the BMI, where there were no significant results for the BMI classes, but it was the LAP, also considered a parameter of adiposity, which was indirectly related to the Lp(a). In a Japanese study, with 2,997 asymptomatic individuals aged between 40 and 69 years, Lp(a) concentrations were shown lower in non-obese individuals (BMI ≥ 26).<a class="elsevierStyleCrossRef" href="#bib0052">52</a>The concentration of GGT in the present study was directly correlated with the concentrations of Lp(a). Since there is a similarity between Lp(a) and the LDL particle, some studies propose that Lp(a) also undergoes an oxidative process as LDL, and during the atherosclerotic process and GGT activity can increase to compensate for the increase in oxidative stimulants, increasing the synthesis of glutathione, which is an important antioxidant.<a class="elsevierStyleCrossRef" href="#bib0001">1</a>,<a class="elsevierStyleCrossRef" href="#bib0053">53</a> A study conducted by Ghatge and collaborators<a class="elsevierStyleCrossRef" href="#bib0054">54</a> also found a positive correlation between the concentrations of Lp(a) and GGT.In this study, PON1 also showed a significant correlation and increased activity in individuals whose Lp(a) concentrations were above 30 mg/dL. This was described in a study with individuals who had moderate to high concentrations of Lp(a).<a class="elsevierStyleCrossRef" href="#bib0055">55</a> It is not yet clear whether PON1 concentrations may have any benefit in individuals with high concentrations of Lp(a).<a class="elsevierStyleCrossRef" href="#bib0055">55</a> The serum concentrations of hsCRP were also correlated to Lp(a), and the comparison between individuals with the presence and absence of plaques was significant by the Man Whitney test (p < 0.02), which may suggest a possible underlying inflammatory process implied by atherosclerosis.<a class="elsevierStyleCrossRef" href="#bib0053">53</a>The present study has certain limitations since it has not analyzed genetic factors that influence the concentration of Lp(a) and the identification of apo (a) isoforms. Another limitation is that only carotid ultrasound was performed and no other arterial systems susceptible to atherosclerosis were examined. Therefore, the outcome could have been different or increased from the present results if the coronary and femoral arteries had been analyzed. Nevertheless, a strict criterion was adopted for the selection of participants, which caused a limited number of individuals, and the analysis of Lp(a) was performed by nephelometry, considered the gold standard for analysis of Lp(a).This study pointed out that Lp(a) concentrations above 30 mg/dL were associated with the presence of carotid plaques in asymptomatic individuals with a median age of 43 years, and a 2% odds ratio for the presence of plaques. In fact, the relationship between Lp(a) and CVD in general, is well established in the literature, however, the strength of these associations and the mechanism in which Lp(a) influences the atherosclerotic process must be explored further." "textoCompletoSecciones" => array:1 [ "secciones" => array:9 [ 0 => array:3 [ "identificador" => "xres1954058" "titulo" => "Highlights" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abss0001" ] ] ] 1 => array:3 [ "identificador" => "xres1954059" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abss0003" "titulo" => "Background" ] 1 => array:2 [ "identificador" => "abss0004" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abss0005" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abss0006" "titulo" => "Conclusion" ] ] ] 2 => array:2 [ "identificador" => "xpalclavsec1682131" "titulo" => "Keywords" ] 3 => array:2 [ "identificador" => "sec0001" "titulo" => "Introduction" ] 4 => array:3 [ "identificador" => "sec0002" "titulo" => "Materials and methods" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "sec0003" "titulo" => "Study population" ] 1 => array:2 [ "identificador" => "sec0004" "titulo" => "Clinical and anthropometrical evaluation" ] 2 => array:2 [ "identificador" => "sec0005" "titulo" => "Biochemical analysis" ] 3 => array:2 [ "identificador" => "sec0006" "titulo" => "Carotid Intima-Media Thickness (cIMT) determination and carotid plaques detection" ] 4 => array:2 [ "identificador" => "sec0007" "titulo" => "Statistical analysis" ] ] ] 5 => array:2 [ "identificador" => "sec0008" "titulo" => "Results" ] 6 => array:2 [ "identificador" => "sec0009" "titulo" => "Discussion" ] 7 => array:2 [ "identificador" => "xack684958" "titulo" => "Acknowledgments" ] 8 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2022-04-22" "fechaAceptado" => "2022-08-29" "PalabrasClave" => array:1 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1682131" "palabras" => array:3 [ 0 => "Lipoprotein (a)" 1 => "Carotid atherosclerosis" 2 => "Carotid plaques" ] ] ] ] "tieneResumen" => true "highlights" => array:2 [ "titulo" => "Highlights" "resumen" => "<ul class="elsevierStyleList" id="celist0001"><li class="elsevierStyleListItem" id="celistitem0001">•High lipoprotein (a) levels increase the risk of carotid plaques presence in asymptomatic subjects.</li><li class="elsevierStyleListItem" id="celistitem0002">•Carotid intima-media thickness is not affected by plasma lipoprotein (a) levels.</li><li class="elsevierStyleListItem" id="celistitem0003">•Age and race are directly associated with lipoprotein (a) levels, suggesting an important influence even in a highly miscegenated population.</li></ul>" ] "resumen" => array:1 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "BackgroundThis study aimed to evaluate the associations between Lipoprotein (a) ‒ Lp(a) levels and carotid Intima-Media Thickness (cIMT) and with carotid plaques in healthy subjects because of previous contradictory data. MethodsA total of 317 healthy normolipidemic subjects (20‒77 years old) were selected. The cIMT and atherosclerotic plaques were determined by B-mode ultrasonography. Mann-Whitney tests were performed to compare the groups according to Lp(a) levels and to explore the associations between Lp(a), carotid plaques, and cIMT, logistic and linear regression analyses were performed. ResultsStudied population (51% females, median age 43 years old) presented carotid plaques and cIMT ≥ 0.9 mm in 23% and 18% of the participants, respectively. The group with Lp(a) levels > 30 mg/dL presented significantly higher age and atherosclerotic plaques. Indeed, multivariate linear regression analysis showed a significant association between Lp(a), age, and race. On the other hand, logistic regression analysis demonstrated that the subjects with Lp(a) > 30 mg/dL have a significantly high risk of carotid plaques. ConclusionThe data from the present study indicate that Lp(a) levels above 30 mg/dL contribute to the development of carotid plaques even in apparently healthy participants." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abss0003" "titulo" => "Background" ] 1 => array:2 [ "identificador" => "abss0004" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abss0005" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abss0006" "titulo" => "Conclusion" ] ] ] ] "multimedia" => array:4 [ 0 => array:8 [ "identificador" => "tbl0001" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0001" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "N, Sample size; Non-whites include: Blacks, mixed races, and asian; BMI, Body mass index; LAP, Lipid accumulation product; SBP, Systolic blood pressure; DBP, Dastolic blood pressure; cIMT, Carotid intima media thickness; HDL-C, High-density lipoprotein cholesterol; NHDL-C, Non-high density lipoprotein cholesterol; LDL-C, Low-density lipoprotein cholesterol; VLDL-C, Very low-density lipoprotein cholesterol; ApoA-I, Apolipoprotein A‒I; ApoB-100, Apolipoprotein B100; Lp(a), Lipoprotein (a); hsCRP, High sensitivity C-reactive protein; PON1, Paraoxonase-1; ALT, Alanine aminotransferase; AST, Aspartate aminotransferase; ALP, Alkaline phosphatase; GGT, Gamma glutamyl transferase; TSH, Thyroid stimulating hormone; FT4, Free thyroxine. Literature used for reference values: Brazilian Guidelines on Obesity 2016 4th edition; World health organization ‒ average body mass index; Brazilian Guideline for Hypertension; Update of the Brazilian guideline on dyslipidemia and prevention of atherosclerosis 2017; Guideline of the Brazilian Diabetes Society; Clinical diagnosis and treatment by laboratory methods 21 edition; Clinical practice guideline for the assessment and management of chronic kidney disease; Brazilian consensus on thyroid. Values are expressed as median and interquartile range (25th and 75th)." "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"><a name="en0001"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">n \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0002"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Median (25th‒75th) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0003"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Parameters \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0004"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0005"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">43 (34‒54) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0006"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Age (years) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0007"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">163/154 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0008"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">‒ \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0009"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Sex (Female/Male) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0010"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">259/58 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0011"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">‒ \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0012"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Race (White/Non-white) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0013"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0014"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">23 (22‒25) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0015"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">BMI (kg/m2) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0016"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0017"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">74 (68‒81) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0018"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Waist circunference (cm) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0019"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">316 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0020"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">92 (88‒98) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0021"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Hips circunference (cm) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0022"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">316 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0023"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.8 (0.7‒0.9) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0024"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Waist-to-hip ratio \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0025"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0026"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.5 (0.4‒0.5) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0027"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Waist-to-height ratio \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0028"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0029"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">9 (4‒17) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0030"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">LAP (cm/mmoL/L) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0031"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0032"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">120 (110‒128) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0033"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">SBP (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0034"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0035"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">80 (72‒80) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0036"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">DBP (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0037"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0038"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.6 (0.5‒0.7) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0039"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Left cIMT (mm) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0040"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0041"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.6 (0.5‒0.7) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0042"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Right cIMT (mm) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0043"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0044"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.6 (0.5‒0.7) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0045"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Mean cIMT mm) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0046"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">58/259 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0047"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">‒ \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0048"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Plaques (Yes/No) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0049"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0050"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">173 (153‒198) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0051"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Total cholesterol (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0052"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0053"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">58 (38‒74) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0054"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">HDL-C (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0055"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0056"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">117 (98‒135) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0057"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">NHDL-C (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0058"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0059"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">73 (55‒95) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0060"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Triglycerides (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0061"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0062"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">101 (85‒120) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0063"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">LDL-C (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0064"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0065"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">15 (11‒19) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0066"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">VLDL-C (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0067"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0068"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">149 (118‒176) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0069"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">ApoA-I (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0070"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0071"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">78 (67‒93) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0072"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">ApoB100 (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0073"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0074"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">12 (4‒26) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0075"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Lp(a) (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0076"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">313 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0077"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.8 (0.4‒1.7) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0078"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">hsCRP (mg/L) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0079"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">315 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0080"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">32 (13‒53) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0081"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">PON1 (µmoL/min) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0082"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0083"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">84 (78‒88) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0084"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Glucose (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0085"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0086"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">30 (25‒35) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0087"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Urea (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0088"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0089"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.8 (0.7‒0.9) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0090"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Creatinine (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0091"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0092"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">4.5 (3.8‒5.4) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0093"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Uric acid (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0094"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0095"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">17 (13‒22) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0096"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">ALT (U/L) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0097"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">297 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0098"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">19 (16‒23) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0099"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">AST (U/L) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0100"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">316 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0101"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">65 (52‒76) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0102"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">ALP (U/L) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0103"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">297 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0104"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">18 (13‒25) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0105"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">GGT (U/L) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0106"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0107"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2 (1.4‒2.9) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0108"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">TSH (uUI/mL) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0109"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0110"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.3 (1.2‒1.4) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0111"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">FT4 (ng/dL) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3252718.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Anthropometric, clinical, and biochemical characteristics of individuals." ] ] 1 => array:8 [ "identificador" => "tbl0002" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0002" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "N, Sample size; Lp(a), Lipoprotein (a); Non-whites included,: Blacks, mixed races, and asian; ApoB-100, Apolipoprotein B100; hsCRP, high sensitivity C-reactive protein; PON1, Activity paraoxonase 1; GGT, Gamma-glutamyltransferase; Values are expressed as interquartile ranges (25th and 75th); significant p-value: ≤ 0.05; the numerical variables were compared by the Mann-Whitney test and the non‒numerical variables by Chi-Square; the variable Lp(a) was transformed into." "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"><a name="en0112"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="top" scope="col">Parameters \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0113"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Lp(a) ≤ 30 mg/dL)</th><a name="en0114"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Lp(a) > 30 mg/dL</th><a name="en0115"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="top" scope="col">p‒value \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr><tr title="table-row"><a name="en0112a"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0117"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">n \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0118"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Median (25th‒75th) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0119"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">n \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0120"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Median (25th‒75th) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0115a"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0122"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Age (years) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0123"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">250 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0124"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">43 (33‒53) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0125"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">67 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0126"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">45 (36‒57) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0127"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.04 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0128"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Race (White/No‒white) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0129"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">215/35 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0130"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0131"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">44/23 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0132"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0133"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0134"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">Plaque (Yes/No) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0135"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">40/210 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0136"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0137"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">18/49 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0138"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0139"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.04 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0140"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " colspan="6" align="left" valign="top">Biochemical parameters</td></tr><tr title="table-row"><a name="en0141"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">ApoB100 (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0142"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">250 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0143"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">76 (65‒91) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0144"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">67 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0145"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">86 (75‒102) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0146"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">< 0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0147"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">hsCRP (mg/L) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0148"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">247 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0149"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.80 (0.40‒1.50) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0150"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">66 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0151"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.93 (0.50‒1.90) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0152"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.07 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0153"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">PON1 (µmoL/min) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0154"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">249 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0155"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">28 (12‒52) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0156"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">66 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0157"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">42 (19‒57) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0158"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0159"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">GGT (U/L) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0160"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">236 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0161"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">17 (13‒23) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0162"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">61 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0163"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">21 (15‒30) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0164"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.02 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3252717.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Significant comparisons of demographic and biochemical variables of individuals by serum Lp(a) concentrations." ] ] 2 => array:8 [ "identificador" => "tbl0003" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0003" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "Linear regression analysis; N, Number of individuals; β, Estimated parameter; significant p-value ≤ 0.05; Non-whites include blacks, mixed races and asian; LAP, Lipid accumulation product; SBP, Systolic blood pressure; DBP, Diastolic 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"><a name="en0165"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0166"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Univariate</th><a name="en0167"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="4" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Multivariate</th></tr><tr title="table-row"><a name="en0168"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Parameters \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0169"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">n \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0170"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Β \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0171"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">p-value \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0172"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">β \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0173"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">R2-partial \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0174"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">R2-total \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0175"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">p-value \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0176"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Age (years) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0177"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0178"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.21 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0179"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">< 0.01 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0180"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.35 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0181"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.02 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0182"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.07 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0183"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">< 0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0184"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Race (White/No-white) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0185"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0186"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">34.73 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0187"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">< 0.01 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0188"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">32.07 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0189"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.04 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0190"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0191"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0192"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">LAP (cm/mmoL/L) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0193"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0194"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">‒0.65 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0195"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.14 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0196"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">-0.87 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0197"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.01 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0198"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0199"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.05 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0200"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">SBP (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0201"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0202"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.93 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0203"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.01 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0204"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0205"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0206"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0207"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0208"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">DBP (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0209"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">317 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0210"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.00 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0211"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.02 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0212"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0213"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0214"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0215"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3252715.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Linear regression analysis between Lp(a) and clinical and anthropometric parameters." ] ] 3 => array:8 [ "identificador" => "tbl0004" "etiqueta" => "Table 4" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0004" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "OR, Odds Ratio; 95% CI, Confidence Interval 95%; Non-whites Include: blacks, mixed races and asian; Lp(a), Lipoprotein (a); p-value ≤ 0.05; Lp(a) was transformed into." "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"><a name="en0216"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0217"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Univariate</th><a name="en0218"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Multivariate</th></tr><tr title="table-row"><a name="en0219"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Parameters \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0220"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">OR \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0221"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">95% CI \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0222"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">p-value \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0223"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">OR \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0224"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">95% CI \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0225"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">p-value \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0226"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Age (years) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0227"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.11 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0228"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.08‒1.1 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0229"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">< 0.01 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0230"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.11 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0231"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.08‒1.1 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0232"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">< 0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0233"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Race (White/No-white) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0234"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.97 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0235"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.0‒3.9 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0236"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.05 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0237"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.50 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0238"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.2‒5.6 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0239"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.02 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0240"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Lp(a) (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0241"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.02 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0242"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.0‒1.0 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0243"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.02 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0244"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0245"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0246"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3252716.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Univariate and multivariate logistic regression analysis for the presence of plaques." ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "cebibsec1" "bibliografiaReferencia" => array:55 [ 0 => array:3 [ "identificador" => "bib0001" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "A test in context: lipoprotein(a)" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "S. 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McCormick" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.jprot.2011.07.008" "Revista" => array:7 [ "tituloSerie" => "J Proteomics" "fecha" => "2011" "volumen" => "74" "numero" => "12" "paginaInicial" => "2881" "paginaFinal" => "2891" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/21802535" "web" => "Medline" ] ] ] ] ] ] ] ] ] ] ] ] "agradecimientos" => array:1 [ 0 => array:4 [ "identificador" => "xack684958" "titulo" => "Acknowledgments" "texto" => "The authors acknowledge the Municipal Health Department of Campinas for furnishing the data and authorization of their use. We thank Dr. Jamal Baraccat from the Department of Radiology at the School of Medical Sciences, State University of Campinas (UNICAMP), for performing the carotid measurements. We thank the Statistics Department, Faculty of Medical Sciences, and UNICAMP for the statistical assistance. This work was supported by the State of Sao Paulo Research Foundation (FAPESP) grant number n° 2006/60585-9 and by Coordination for the Improvement of Higher Education Personnel (CAPES) ‒ Brazil – Grant number 88882.434895/2019-01." "vista" => "all" ] ] ] "idiomaDefecto" => "en" "url" => "/18075932/000000770000000C/v3_202308251443/S1807593222033087/v3_202308251443/en/main.assets" "Apartado" => array:4 [ "identificador" => "94924" "tipo" => "SECCION" "en" => array:2 [ "titulo" => "Original articles" "idiomaDefecto" => true ] "idiomaDefecto" => "en" ] "PDF" => "https://static.elsevier.es/multimedia/18075932/000000770000000C/v3_202308251443/S1807593222033087/v3_202308251443/en/main.pdf?idApp=UINPBA00004N&text.app=https://www.elsevier.es/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S1807593222033087?idApp=UINPBA00004N"]

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Victor Françaa,

Corresponding author

victtor_franca@hotmail.com

Corresponding author.

, Érica Ivana Lázaro Gomesa, Edite Vieira Silva de Camposa, Vanessa Helena de Souza Zagob, Valéria Sutti Nunesc, Eliana Cotta de Fariaa

a Department of Clinical Pathology, Faculdade de Ciências Médicas da Universidade Estadual de Campinas, Campinas, SP, Brazil

b Pontifical Catholic University of Campinas, São Paulo, Brazil

c Laboratorio de Lipides (LIM10), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, BR

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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0001" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0008">Introduction</span><p id="para0008" class="elsevierStylePara elsevierViewall">Lipoprotein &#40;a&#41; &#8210; Lp&#40;a&#41; is a lipoprotein fraction similar to the Low-Density Lipoprotein &#40;LDL&#41;&#44; that contains an apolipoprotein &#40;a&#41; linked to its structure&#46; Plasma levels of Lp&#40;a&#41; display a wide range in the general population and is primarily controlled by hepatic synthesis of apo &#40;a&#41;&#44; which in turn varies according to the presence of polymorphisms in the <span class="elsevierStyleItalic">LPA</span> gene&#46;<a class="elsevierStyleCrossRef" href="#bib0001"><span class="elsevierStyleSup">1</span></a> Despite the similarities with plasminogen structure&#44; apolipoprotein &#40;a&#41; contains only the Kringle &#40;K&#41; IV and V in its structure&#46; Among the subtypes of KIV&#44; specifically&#44; subtype two of KIV &#40;KIV2&#41; presents a variable number of copies&#44; reaching more than&#160;40&#44; thus it is possible to reach up to&#160;34&#160;different apo &#40;a&#41; isoforms&#46;<a class="elsevierStyleCrossRef" href="#bib0002"><span class="elsevierStyleSup">2</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0003"><span class="elsevierStyleSup">3</span></a></p><p id="para0009" class="elsevierStylePara elsevierViewall">Levels of Lp&#40;a&#41; are considered an independent risk factor for cardiovascular disease according to epidemiologic and genetic studies carried out in different populations&#46; In spite of it&#44; reference risk values are not usually adopted&#46;<a class="elsevierStyleCrossRef" href="#bib0001"><span class="elsevierStyleSup">1</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0004"><span class="elsevierStyleSup">4</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">5</span></a></p><p id="para0010" class="elsevierStylePara elsevierViewall">Lp&#40;a&#41; levels remain relatively constant in an individual throughout life and are not significantly affected by diet&#44; age&#44; and physical activity&#46;<a class="elsevierStyleCrossRef" href="#bib0006"><span class="elsevierStyleSup">6</span></a> Still&#44; they vary according to ethnicity&#58; individuals of African American descent have two to three times higher concentrations compared to Caucasians<a class="elsevierStyleCrossRef" href="#bib0007"><span class="elsevierStyleSup">7</span></a> although Lp&#40;a&#41; levels may have a greater influence on plaque burden in white than in black individuals&#46;<a class="elsevierStyleCrossRef" href="#bib0008"><span class="elsevierStyleSup">8</span></a></p><p id="para0011" class="elsevierStylePara elsevierViewall">The association of Lp&#40;a&#41; and cardiovascular diseases is justified by the atherogenic risk attached to the LDL structure and is aggravated by the similarity of apo &#40;a&#41; structure to plasminogen that could interfere in hemostasis&#46; This effect may explain the role of Lp&#40;a&#41; in the promotion of cardiovascular diseases&#44; eventually favoring atherogenic and prothrombotic processes&#46;<a class="elsevierStyleCrossRef" href="#bib0001"><span class="elsevierStyleSup">1</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0009"><span class="elsevierStyleSup">9</span></a></p><p id="para0012" class="elsevierStylePara elsevierViewall">There is evidence that high Lp&#40;a&#41; levels&#44; especially above&#160;30&#160;mg&#47;dL&#44; contribute to the progression of atherosclerotic plaque and increased carotid Intima-Media Thickness &#40;cIMT&#41;&#46;<a class="elsevierStyleCrossRefs" href="#bib0010"><span class="elsevierStyleSup">10&#8211;13</span></a> However&#44; this issue remains under debate&#46; While some studies associate Lp&#40;a&#41; independently with cIMT and plaque development&#44; other studies have not shown such an association&#46;<a class="elsevierStyleCrossRefs" href="#bib0014"><span class="elsevierStyleSup">14&#8211;18</span></a> Furthermore&#44; given the important role of Lp&#40;a&#41; in the development of cardiovascular diseases&#44; the present study aimed to explore the association between Lp&#40;a&#41; levels and subclinical carotid atherosclerosis measured as cIMT as well as the presence of carotid plaques in asymptomatic individuals&#46;</p></span><span id="sec0002" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0009">Materials and methods</span><span id="sec0003" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0010">Study population</span><p id="para0013" class="elsevierStylePara elsevierViewall">This is a cross-section&#44; retrospective study&#44; for which were selected&#160;317&#160;individuals from both genders&#44; aged between&#160;19&#160;and&#160;77&#160;years old&#44; between the years&#160;2008 and&#160;2013&#44; who participated in the FAPESP Thematic Project&#160;2006&#47;60585-9&#44; after authorization by the Research Ethics Committee of the Faculty of Medical Sciences&#47;UNICAMP&#46; The study was carried out in accordance with the Declaration of Helsinki&#46;</p><p id="para0014" class="elsevierStylePara elsevierViewall">This project was carried out in partnership with the Municipal Health Department of Campinas&#44; which provided the laboratory results of the lipid profile of individuals who spontaneously sought healthcare in the Basic Health Units of the city of Campinas&#44; S&#227;o Paulo&#44; Brazil&#46; As previously reported by Parra et al&#46;<a class="elsevierStyleCrossRef" href="#bib0019"><span class="elsevierStyleSup">19</span></a> the volunteers were initially selected according to plasma LDL-C &#40;&#8804; 130&#160;mg&#47;dL&#41; and triglycerides &#40;&#8804; 150&#160;mg&#47;dL&#41; levels&#46; Thus&#44; they were contacted by telephone and answered a screening questionnaire regarding medication use&#44; Body Mass Index &#40;BMI&#41;&#44; and current and pre-existing diseases&#46; The individuals who met the inclusion criteria were invited to attend clinical and laboratory evaluations&#46;</p><p id="para0015" class="elsevierStylePara elsevierViewall">On admission&#44; all volunteers signed the Informed Consent Form &#40;ICF&#41; before a complete clinical&#44; anthropometric&#44; and laboratory evaluation&#46; Peripheral venous blood samples were drawn in EDTA-containing tubes after a&#160;12-hour fasting period&#46; Serum and plasma were separated by centrifugation &#40;4&#176;C&#44; 1000g&#44; 10&#160;minutes&#41; and stored at&#160;-80&#176;C until further analysis&#46;</p><p id="para0016" class="elsevierStylePara elsevierViewall">The inclusion criteria were both genders&#44; BMI between&#160;20 and&#160;30&#160;kg&#47;m<span class="elsevierStyleSup">2</span>&#59; LDL-C&#160;&#8804; 130&#160;mg&#47;dL and triglycerides&#160;&#8804; 150&#160;mg&#47;dL levels&#44; Systolic Blood Pressure &#40;SBP&#41;&#160;&#8804; 140&#160;mmHg or Diastolic Blood Pressure &#40;DBP&#41;&#160;&#8804; 90&#160;mmHg&#46; Exclusion criteria comprised BMI higher than&#160;30&#160;kg&#47;m<span class="elsevierStyleSup">2</span>&#44; regular use of medical treatment&#44; especially those which interfere with lipids metabolism &#40;statins&#44; fibrates&#44; oral contraceptives&#44; and hormonal replacement therapy&#41;&#44; and clinical and&#47;or laboratory evidence of thyroid dysfunction&#44; dyslipidemia&#44; diabetes&#44; metabolic syndrome&#44; pregnancy&#44; hypertension&#44; liver&#44; kidney or pulmonary disease&#44; alcoholism&#44; and smoking&#46; Individuals who attend the inclusion criteria were invited to undergo carotid ultrasonography in a second visit&#46;</p></span><span id="sec0004" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0011">Clinical and anthropometrical evaluation</span><p id="para0017" class="elsevierStylePara elsevierViewall">Volunteers answered a detailed questionnaire regarding their medical history&#44; and their race was self-reported as white&#44; black&#44; or mixed&#46;</p><p id="para0018" class="elsevierStylePara elsevierViewall">Determinations included systolic and diastolic blood pressure &#40;SBP and DBP&#44; respectively&#41; body weight &#40;kg&#41;&#44; height &#40;cm&#41;&#44; and circumferences of the waist and hips &#40;WC&#44; cm&#41;&#46; Thus&#44; BMI&#44; waist-to-hip and waist-to-height ratios&#44; all considered adiposity markers were calculated&#46;<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">20</span></a> The Lipid Accumulation Product &#40;LAP&#41; was also calculated according to the waist circumference and triglycerides levels &#40;mmoL&#47;dL&#41; as described previously&#46;<a class="elsevierStyleCrossRef" href="#bib0021"><span class="elsevierStyleSup">21</span></a></p></span><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0012">Biochemical analysis</span><p id="para0019" class="elsevierStylePara elsevierViewall">Total Cholesterol &#40;TC&#41;&#44; High-Density Lipoprotein Cholesterol &#40;HDL-C&#41;&#44; triglycerides&#44; glucose&#44; uric acid&#44; urea&#44; alanine aminotransferase&#44; aspartate aminotransferase&#44; gamma-glutamyl transferase&#44; creatinine and alkaline phosphatase were determined in the automatized system Modular&#174; Analytics Evo &#40;Roche Diagnostics&#44; Burgess Hill&#44; West Sussex&#44; UK&#41; using commercially available Roche Diagnostics&#174; &#40;Mannheim&#44; Germany&#41; assays&#46; Thyroid Stimulation Hormone &#40;TSH&#41; and Thyroxin &#40;T4L&#41; were also determined in the automated system Elecsys&#160;2010 &#40;Roche&#44; Basel&#44; Switzerland&#41; using Roche Diagnostics&#174; &#40;Mannheim&#44; Germany&#41; assays&#46;</p><p id="para0020" class="elsevierStylePara elsevierViewall">Low-Density Lipoprotein Cholesterol &#40;LDL-C&#41;&#44; and Very-Low Density Lipoprotein Cholesterol &#40;VLDL-C&#41; were determined by Friedewald&#39;s equation&#44; and by triglycerides&#47;5&#44; respectively&#44;<a class="elsevierStyleCrossRef" href="#bib0022"><span class="elsevierStyleSup">22</span></a> Non-HDL Cholesterol &#40;NHDL-C&#41; were calculated by subtracting the HDL-C levels from total cholesterol&#46;</p><p id="para0021" class="elsevierStylePara elsevierViewall">Apolipoproteins A-I &#40;apo A-I&#41;&#44; B-100 &#40;apo&#160;B-100&#41; and &#91;Lp&#40;a&#41;&#93; were determined by nephelometry in the automated system BN II &#40;Siemens Healthcare Diagnostics&#44; Marburg&#44; Germany&#41; using commercially available assays &#40;Dade-Boehringer&#174;&#44; Deerfield&#44; IL&#44; USA&#41;&#46; C-Reactive Protein &#40;CRP&#41; was measured by immunoturbidimetry using the Tina-quant&#174; CRP &#40;latex&#41; high-sensitivity assay &#40;Roche Diagnostics&#174;&#44; Mannheim&#44; Germany&#41;&#46;</p><p id="para0022" class="elsevierStylePara elsevierViewall">Plasma Paraoxonase-1 activity &#40;PON1&#41; was evaluated through an enzymatic method using paraoxon &#40;diethyl-p-nitrophenylphosphate&#44; Sigma&#44; St&#46; Louis&#44; MO&#41; as substrate&#46;<a class="elsevierStyleCrossRef" href="#bib0023"><span class="elsevierStyleSup">23</span></a></p></span><span id="sec0006" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0013">Carotid Intima-Media Thickness &#40;cIMT&#41; determination and carotid plaques detection</span><p id="para0023" class="elsevierStylePara elsevierViewall">The determinations of cIMT and plaques were performed by a single trained radiologist&#44; blind to the study participants&#46; Determinations were made by high-resolution B-mode ultrasonography using a&#160;6&#8211;9&#160;MHz linear array ultrasound imaging system ATL HDI&#160;3500 Ultrasound System &#40;Advanced Technology Laboratories Ultrasound&#44; Bothell&#44; USA&#41;&#46; The volunteers were examined in dorsal decubitus and five longitudinal measurements of segments of left&#44; and right common carotid arteries at the distal wall and 1&#160;cm from the bifurcation were performed&#46; Mean cIMT &#40;mm&#41; was calculated as the average of these measurements&#44; and cIMT below&#160;0&#46;90&#160;mm was considered a normal reference&#46;<a class="elsevierStyleCrossRef" href="#bib0024"><span class="elsevierStyleSup">24</span></a> In addition&#44; it was considered as plaque the presence of at least one of the following parameters&#58; focal wall thickening with at least&#160;0&#46;5&#160;mm toward the vessel lumen&#44; focal wall thickening at least&#160;50&#37; greater than that of the surrounding vessel wall&#44; or focal region with cIMT above&#160;1&#46;5&#160;mm that protrudes into the lumen that is distinct from the adjacent boundary&#46;<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">25</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0026"><span class="elsevierStyleSup">26</span></a></p></span><span id="sec0007" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0014">Statistical analysis</span><p id="para0024" class="elsevierStylePara elsevierViewall">The statistical analyses were performed using the software SAS&#160;9&#46;2 &#40;SAS Institute Inc&#46;&#44; Cary&#44; NC&#44; USA&#41; and the SPSS&#160;16&#46;0 &#40;SPSS Inc&#46; Released 2007&#46; SPSS for Windows&#44; Version&#160;16&#46;0&#46; Chicago&#44; SPSS Inc&#46;&#41;&#46; A two-sided p-value&#160;&#8804; 0&#46;05 was considered statistically significant&#44; and p-values&#160;&#62; 0&#46;05 and&#160;&#60; 0&#46;08 were determined as borderline&#46;</p><p id="para0025" class="elsevierStylePara elsevierViewall">Data normality was verified by the Shapiro-Wilk test&#46; Due to the absence of normal distribution&#44; numeric data were expressed as median and interquartile ranges and were adopted non-parametric tests&#46; In order to explore the relationship between Lp&#40;a&#41; and the studied variables&#44; the Spearman correlation test was performed&#46; In addition&#44; the parameters were compared by the Mann-Whitney test according to Lp&#40;a&#41; levels &#40;&#8804; 30&#160;mg&#47;dL and &#62; 30&#160;mg&#47;dL&#41;&#46;</p><p id="para0026" class="elsevierStylePara elsevierViewall">Univariate and multivariate linear regression analyses were performed to evaluate the influence of Lp&#40;a&#41; levels on the other studied parameters&#46; Numeric variables were transformed into ranks due to the absence of normal distribution&#44; and the results were as coefficients of determination &#40;partial R<span class="elsevierStyleSup">2</span> and R<span class="elsevierStyleSup">2</span>&#41;&#46; Logistic regression analysis was performed in order to determine the Odds Ratio &#40;OR&#41; for plaque presence in the studied population&#46;</p></span></span><span id="sec0008" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0015">Results</span><p id="para0027" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0001">Table 1</a> presents the descriptive analysis for clinical&#44; anthropometrical&#44; and biochemical parameters&#46; The total population &#40;n&#160;&#61;&#160;317&#59; 51&#37;&#160;female&#41; was asymptomatic&#44; with normal weight&#44; blood pressure&#44; and plasma lipids&#44; in accordance with the respective guidelines adopted&#46;<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">20</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRefs" href="#bib0027"><span class="elsevierStyleSup">27&#8211;29</span></a> Among the volunteers&#44; 23&#37;&#160;present increased cIMT &#40;&#8805;0&#46;90&#160;mm&#41;&#44; and 18&#37; were identified with carotid plaques&#46;</p><elsevierMultimedia ident="tbl0001"></elsevierMultimedia><p id="para0028" class="elsevierStylePara elsevierViewall">The variables were compared between groups stratified according to Lp&#40;a&#41; levels &#40;<a class="elsevierStyleCrossRef" href="#tbl0002">Table 2</a>&#41;&#46; The group with levels above&#160;30&#160;mg&#47;Dl&#160;&#40;21&#37;&#41; exhibited a higher median age&#44; apolipoprotein B-100&#44; PON1 activity&#44; and GGT levels&#46; In addition&#44; the presence of plaques and non-white individuals was also significantly more frequent in this group&#46;</p><elsevierMultimedia ident="tbl0002"></elsevierMultimedia><p id="para0029" class="elsevierStylePara elsevierViewall">Spearman&#39;s correlation between Lp&#40;a&#41; and the other parameters revealed positive and significant correlations with age &#40;R&#160;&#61;&#160;0&#46;167&#59; p &#60; 0&#46;01&#41;&#44; SBP &#40;R&#160;&#61;&#160;0&#46;136&#59; p &#60; 0&#46;02&#41;&#44; DBP &#40;R&#160;&#61;&#160;0&#46;109&#59; p&#160;&#61;&#160;0&#46;05&#41;&#44; ApoB-100 &#40;R&#160;&#61;&#160;0&#46;258&#59; p &#60; 0&#46;01&#41;&#44; PON1 &#40;R&#160;&#61;&#160;0&#46;108&#59; p&#160;&#61;&#160;0&#46;05&#41;&#44; GGT &#40;R&#160;&#61;&#160;0&#46;123&#59; p&#160;&#61;&#160;0&#46;03&#41;&#44; hsCRP &#40;R&#160;&#61;&#160;0&#46;157&#59; p &#60; 0&#46;01&#41;&#44; and a tendency towards cIMT &#40;R&#160;&#61;&#160;0&#46;099&#59; p&#160;&#61;&#160;0&#46;08&#41;&#46;</p><p id="para0030" class="elsevierStylePara elsevierViewall">The possible associations between Lp&#40;a&#41; and the other variables were explored in the analysis of univariate and multivariate linear regression&#44; whose significant parameters are shown in <a class="elsevierStyleCrossRef" href="#tbl0003">Table 3</a>&#46; Direct and significant associations with age and race were observed&#44; both in the univariate and multivariate analyses&#46; SBP and DBP are also directly associated with Lp&#40;a&#41; in univariate analysis&#44; however&#44; they did not show significance in multivariate analysis&#46; The LAP&#44; an adiposity parameter&#44; was indirectly related to Lp&#40;a&#41; in both univariate and multivariate analyses&#46;</p><elsevierMultimedia ident="tbl0003"></elsevierMultimedia><p id="para0031" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0004">Table 4</a> shows the analysis of univariate and multivariate logistic regression to explore the association between the presence of plaques&#44; Lp&#40;a&#41;&#44; and other parameters&#46; With each year of life&#44; the odds ratio for plaque increases by about&#160;1&#46;11&#160;times&#160;&#40;11&#37;&#41;&#46; For non-white individuals&#44; the odds ratio for the plaque is approximately&#160;1&#46;97&#160;times&#160;&#40;97&#37;&#41; in univariate&#44; and&#160;2&#46;5&#160;times&#160;&#40;250&#37;&#41; in the multivariate analysis&#46; Regarding Lp&#40;a&#41; concentrations above&#160;30&#160;mg&#47;dL&#44; there is a&#160;2&#37;&#160;increase in the odds ratio for plaque in univariate analysis&#46;</p><elsevierMultimedia ident="tbl0004"></elsevierMultimedia></span><span id="sec0009" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0016">Discussion</span><p id="para0032" class="elsevierStylePara elsevierViewall">The present study investigated the possible relationships between plasma Lp&#40;a&#41; levels and subclinical atherosclerosis determined by cIMT&#44; as well as the presence of carotid plaques in asymptomatic adults&#46; The group selected for this study consisted of individuals of both genders&#44; predominantly self-declared as white &#40;82&#37;&#41; and clinically assessed as normotensive&#44; normolipidemic&#44; and eutrophic&#44; with no evidence of pre-established cardiovascular diseases or other pathologies&#46; In addition&#44; the group consists of adults &#40;with a median age of&#160;43&#160;years&#41;&#44; of whom carotid plaques were reported in&#160;18&#37;&#46;</p><p id="para0033" class="elsevierStylePara elsevierViewall">The contribution of cIMT to the prediction of cardiovascular risk is widely reported in the literature&#44; and the presence of plaques adds significant value to this determination illustrating the heterogeneity of the atherosclerotic disease&#46; On the one hand&#44; the cIMT reflects the thickening process of the intima-medial layer that normally increases with age and smooth muscle hypertrophy&#46; In contrast&#44; the presence of plaques is specific and shows the established atherosclerotic disease&#46;<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">30</span></a></p><p id="para0034" class="elsevierStylePara elsevierViewall">The occurrence of carotid atherosclerotic plaques is recognized to increase with age&#44; however&#44; the prevalence in populations can vary significantly according to the methods applied for its determination and the definition of plaque adopted&#46; Another sensitive point is the population itself&#44; concerning the presence of comorbidities&#44; lifestyle&#44; and type of diet&#44; among other factors&#46; For example&#44; Ihle-Hansen and colleagues<a class="elsevierStyleCrossRef" href="#bib0031"><span class="elsevierStyleSup">31</span></a> evaluated cIMT and the presence of plaques in&#160;3683&#160;individuals aged between&#160;63 and 65&#160;years&#59; in this group&#44; 87&#37;&#160;had carotid plaques&#46; Not surprisingly&#44; the presence of risk factors was significant&#44; of which hypertension&#160;&#40;62&#37;&#41;&#44; hypercholesterolemia&#160;&#40;53&#37;&#41;&#44; obesity&#160;&#40;23&#37;&#41;&#44; and diabetes mellitus&#160;&#40;11&#37;&#41; stand out&#46; In this sense&#44; age plus the presence of these other well-established risk factors explain this high plaque prevalence&#46; Other studies in the general population corroborate the high prevalence of atherosclerotic plaques according to the age group and the presence of other risk factors&#44; whose severity increases significantly as these clinical aspects add up&#46;<a class="elsevierStyleCrossRef" href="#bib0032"><span class="elsevierStyleSup">32</span></a> Recently&#44; Song P&#46; and collaborators evaluated from a robust meta-analysis that the prevalence of atherosclerotic plaques in the population between&#160;30&#160;and&#160;79&#160;years is&#160;21&#46;13&#37;&#44; which is equivalent to more than&#160;800&#160;million people&#46;<a class="elsevierStyleCrossRef" href="#bib0033"><span class="elsevierStyleSup">33</span></a></p><p id="para0035" class="elsevierStylePara elsevierViewall">Studies assessing the cIMT and the prevalence of plaques in asymptomatic individuals and their association with non-established risk factors such as Lp&#40;a&#41; are scarce&#46; A study with 6617&#160;Chinese&#44; with no history of CVD&#44; diabetes mellitus&#44; hypertension&#44; and smoking found a mean cIMT of&#160;0&#46;60&#160;mm&#44; considering their age was&#160;49&#46;7 &#177; 5&#46;3&#46;<a class="elsevierStyleCrossRef" href="#bib0034"><span class="elsevierStyleSup">34</span></a> Regarding plaques&#44; the prevalence was&#160;9&#37;&#44; lower than that observed in the present study&#46; This finding&#44; on the one hand&#44; points to the possibility of the presence of an underlying factor&#44; hypothetically Lp&#40;a&#41;&#44; which&#44; apart from traditional factors&#44; may contribute to this relatively high prevalence&#46; On the other hand&#44; it shows the challenge in interpreting parameters that vary according to the technique used&#44; location and number of measurements&#44; number of individuals enrolled&#44; and software algorithm analysis&#46; In this sense&#44; it is possible to state that cIMT and plaques are unlikely to be directly compared&#44; even among groups of healthy individuals&#46;</p><p id="para0036" class="elsevierStylePara elsevierViewall">As expected&#44; age was a factor strongly associated with carotid plaques in this study&#44; although it was composed of healthy individuals&#46; However&#44; the association between Lp&#40;a&#41; levels higher than&#160;30&#160;mg&#47;dL&#44; and the odds ratio for plaques in the univariate analysis suggests a relationship that can be explored&#46; Tsimikas and colleagues &#40;1&#41; reported the presence of apo &#40;a&#41; in atherosclerotic plaques&#44; suggesting that Lp&#40;a&#41; in high concentrations may contribute to plaque progression&#46; There was a positive association between Lp&#40;a&#41; and carotid atherosclerosis in adults with ischemic stroke aged&#160;16&#160;to&#160;54&#160;years in France&#46;<a class="elsevierStyleCrossRef" href="#bib0012"><span class="elsevierStyleSup">12</span></a> The Lp&#40;a&#41; has also been associated with the development of atherosclerosis in individuals with primary hypercholesterolemia and Lp&#40;a&#41; concentrations greater than&#160;50&#160;mg&#47;dL in a group of individuals aged&#160;18&#160;to&#160;80&#160;years in Spain&#46;<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">35</span></a> Hippe and colleagues<a class="elsevierStyleCrossRef" href="#bib0013"><span class="elsevierStyleSup">13</span></a> reported that Lp&#40;a&#41; concentrations greater than&#160;64&#160;mg&#47;dL were independent predictors of carotid plaque progression in individuals with established cardiovascular disease&#44; even maintaining serum LDL-C concentrations below&#160;70&#160;mg&#47;dL&#46; However&#44; Huffman and colleagues<a class="elsevierStyleCrossRef" href="#bib0018"><span class="elsevierStyleSup">18</span></a> did not find an association between Lp&#40;a&#41; concentrations and atherosclerosis among South Asians living in America aged&#160;40&#160;to&#160;84&#160;years without cardiovascular disease&#46; Some studies independently associate Lp&#40;a&#41; with cIMT and carotid atherosclerotic plaques&#44; other studies&#44; however&#44; do not show this correlation&#44; and others in turn report that Lp&#40;a&#41; is more associated with established CVD than in asymptomatic individuals&#44; once that Lp&#40;a&#41; concentrations tend to increase in chronic inflammatory processes&#44; such as rheumatoid arthritis and systemic lupus erythematosus&#46;<a class="elsevierStyleCrossRef" href="#bib0002"><span class="elsevierStyleSup">2</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0003"><span class="elsevierStyleSup">3</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0014"><span class="elsevierStyleSup">14</span></a></p><p id="para0037" class="elsevierStylePara elsevierViewall">In this study&#44; no correlation was found between Lp&#40;a&#41; and cIMT&#46; Nonetheless&#44; Knoflach and collaborators<a class="elsevierStyleCrossRef" href="#bib0036"><span class="elsevierStyleSup">36</span></a> found a direct association between Lp&#40;a&#41; and cIMT in asymptomatic Austrian women aged&#160;18&#160;to&#160;22&#160;similarly to the study by Schreiner and collaborators<a class="elsevierStyleCrossRef" href="#bib0037"><span class="elsevierStyleSup">37</span></a> that found a positive correlation between Lp&#40;a&#41; and cIMT in Americans aged&#160;45&#160;to&#160;64&#44; suggesting that Lp&#40;a&#41; may be associated with development subclinical carotid atherosclerosis&#46; However&#44; Calmarza and colleagues<a class="elsevierStyleCrossRef" href="#bib0016"><span class="elsevierStyleSup">16</span></a> did not find such an association in a study of&#160;172&#160;asymptomatic Spanish individuals aged&#160;43&#160;to&#160;93&#160;years&#46; This association is&#44; in fact&#44; a sensitive point for analysis&#44; since the increase in cIMT can be associated with carotid plaque&#44; however&#44; cIMT cannot be considered an independent predictor of the development of carotid plaque&#44; although these events often coexist and share some vascular determinants common&#46;<a class="elsevierStyleCrossRef" href="#bib0038"><span class="elsevierStyleSup">38</span></a></p><p id="para0038" class="elsevierStylePara elsevierViewall">It is agreed that the plasma concentrations of Lp&#40;a&#41; are genetically determined more specifically by the presence of polymorphisms in the <span class="elsevierStyleItalic">LPA</span> gene that determine the size of the type 2 kringle IV peptide chain &#40;KIV-2&#41; &#40;3&#41;&#46; Thus&#44; the larger the size of KIV-2&#44; the greater the Lp&#40;a&#41;&#59; in contrast&#44; its plasma concentration is lower&#46; This reverse process is associated with the easier removal of larger particles&#44; while smaller ones tend to remain in circulation for longer periods&#46;<a class="elsevierStyleCrossRef" href="#bib0009"><span class="elsevierStyleSup">9</span></a> Evidence points to the participation of LDLR in the removal process&#44; including as a therapeutic target for reducing plasma Lp&#40;a&#41; concentrations&#46; Nonetheless&#44; many contradictions regarding the results observed with statins and PCSK9 inhibitors must be considered&#46;<a class="elsevierStyleCrossRef" href="#bib0001"><span class="elsevierStyleSup">1</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0003"><span class="elsevierStyleSup">3</span></a></p><p id="para0039" class="elsevierStylePara elsevierViewall">Given the complexity of this lipoprotein&#44; reference values have not been defined for the general population&#46; In fact&#44; studies in different ethnic and population groups point to a wide range&#46; Thus&#44; some studies indicate that values above&#160;50&#160;mg&#47;dL &#40;125&#160;nmoL&#47;L&#41; or the&#160;80<span class="elsevierStyleSup">th</span>&#160;percentile are considered high&#46;<a class="elsevierStyleCrossRef" href="#bib0009"><span class="elsevierStyleSup">9</span></a> Other studies&#44; on the other hand&#44; adopt the&#160;30&#160;mg&#47;dL cut&#46;<a class="elsevierStyleCrossRef" href="#bib0001"><span class="elsevierStyleSup">1</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0008"><span class="elsevierStyleSup">8</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0009"><span class="elsevierStyleSup">9</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRefs" href="#bib0039"><span class="elsevierStyleSup">39&#8211;42</span></a> In fact&#44; 21&#37;&#160;of the recruited individuals had Lp&#40;a&#41; above this value&#46; Some studies show that around&#160;30&#37; of the world population has high Lp&#40;a&#41;&#44; which represents approximately two billion individuals&#46;<a class="elsevierStyleCrossRef" href="#bib0001"><span class="elsevierStyleSup">1</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0009"><span class="elsevierStyleSup">9</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0018"><span class="elsevierStyleSup">18</span></a> The Lp&#40;a&#41; concentrations in the asymptomatic individuals of the present study were expressed with a median of&#160;12&#160;mg&#47;dL &#40;4&#8210;26<span class="elsevierStyleSup">th</span>&#160;percentiles&#41;&#44; indicating great similarity with other studies&#46;<a class="elsevierStyleCrossRef" href="#bib0043"><span class="elsevierStyleSup">43</span></a> In a study with Brazilian individuals aged&#160;46&#160;to&#160;68&#160;years&#44; to verify a possible association between concentrations of Lp&#40;a&#41; and coronary artery disease&#44; the control group showed average concentrations of&#160;11&#160;mg&#47;dL of Lp&#40;a&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0044"><span class="elsevierStyleSup">44</span></a> Another study carried out in the city of Ouro Preto&#44; state of Minas Gerais&#44; Brazil&#44; with&#160;400&#160;asymptomatic individuals&#44; showed Lp&#40;a&#41; concentrations with a median of&#160;18&#46;11&#160;mg&#47;dL with an average age of&#160;45&#160;years&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">45</span></a> Schoolchildren averaging&#160;10&#160;years-old&#44; also demonstrated Lp&#40;a&#41; concentrations with a median of&#160;25&#46;5&#160;mg&#47;dL in the Ouro Preto study&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">45</span></a> A recent study involving&#160;4&#44;140&#160;individuals in a cardiovascular reference center in S&#227;o Paulo&#44; showed an average Lp&#40;a&#41; concentration of&#160;24&#46;8&#160;mg&#47;dL&#46;<a class="elsevierStyleCrossRef" href="#bib0046"><span class="elsevierStyleSup">46</span></a></p><p id="para0040" class="elsevierStylePara elsevierViewall">In addition&#44; interesting relationships were observed in this study between Lp&#40;a&#41; levels and race&#46; Several shreds of evidence in the literature point to those non-white individuals having higher concentrations of Lp&#40;a&#41;&#44; about two to three times higher than Caucasians or Orientals&#44; revealing that there is ethnic variability between different population groups&#44; whose underlying causes have not yet been fully understood&#46;<a class="elsevierStyleCrossRef" href="#bib0003"><span class="elsevierStyleSup">3</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0047"><span class="elsevierStyleSup">47</span></a></p><p id="para0041" class="elsevierStylePara elsevierViewall">It was possible to perceive in the present study that serum Lp&#40;a&#41; concentrations in non-white individuals were higher&#44; with a median of&#160;22&#46;85&#160;mg&#47;dL &#40;5&#8210;36&#160;percentiles&#41;&#44; and in white individuals with a median of&#160;11&#46;10&#160;mg&#47;dL &#40;4&#8210;22&#160;percentiles&#41;&#44; with the significance level of&#160;p &#60; 0&#46;01 when compared by the Mann-Whitney test&#46; These concentrations can be partially explained by variations in the <span class="elsevierStyleItalic">LPA</span> locus&#44; mainly by the polymorphism of the apo &#40;a&#41; gene &#40;LPA&#59; MIM&#160;152200&#41;&#46; Among the variants&#44; notably Schmidt and colleagues evaluated three SNPs and reported that they contribute to different concentrations of Lp&#40;a&#41; in African-American and Caucasian individuals&#46;<a class="elsevierStyleCrossRef" href="#bib0047"><span class="elsevierStyleSup">47</span></a> Two SNPs &#40;T3888P and G&#160;&#43;&#160;1&#47;inKIV-8A&#41;&#44; suppressing the Lp&#40;a&#41; set&#44; were more common in Caucasians&#44; while the third SNP &#40;G-21A&#41; increased the activity of promoting apo &#40;a&#41;&#44; this being more common in African Americans&#46;<a class="elsevierStyleCrossRef" href="#bib0003"><span class="elsevierStyleSup">3</span></a></p><p id="para0042" class="elsevierStylePara elsevierViewall">Other studies looked at different populations and found low concentrations also in non-Hispanic Caucasians with a median of&#160;12&#160;mg&#47;dL &#40;5&#8210;32&#160;percentiles&#41;&#44; in Chinese with a median of&#160;11&#160;mg&#47;dL &#40;5&#8210;26&#160;percentiles&#41;&#44; in Japanese with a median of&#160;13&#160;mg&#47;dL &#40;5&#8210;26&#160;percentiles&#41;&#44; and in Hispanics with a median of&#160;19&#160;mg&#47;dL &#40;8&#8210;43&#160;percentiles&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0001"><span class="elsevierStyleSup">1</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0003"><span class="elsevierStyleSup">3</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0009"><span class="elsevierStyleSup">9</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0047"><span class="elsevierStyleSup">47</span></a> Even with different concentrations and isoforms in some populations&#44; Lp&#40;a&#41; was associated positively and similarly with the risk of cardiovascular events in a&#160;20-year longitudinal follow-up study among Caucasian individuals and individuals of African descent&#46;<a class="elsevierStyleCrossRef" href="#bib0001"><span class="elsevierStyleSup">1</span></a> Given this&#44; there is still a lot of discussion about the concentrations considered adequate for Lp&#40;a&#41; due to the great miscegenation of the population&#44; mainly in countries like Brazil&#46;<a class="elsevierStyleCrossRef" href="#bib0006"><span class="elsevierStyleSup">6</span></a></p><p id="para0043" class="elsevierStylePara elsevierViewall">Other factors such as age&#44; sex&#44; and environmental conditions do not have a major influence on Lp&#40;a&#41; concentrations in most studies&#46; However&#44; in the present study&#44; Lp&#40;a&#41; concentrations greater than&#160;30&#160;mg&#47;dL were found in older individuals&#46; Some studies suggest that among adults&#44; Lp&#40;a&#41; concentrations have been somewhat variable&#44; and an association between Lp&#40;a&#41; and longevity has been suggested among the elderly&#46;<a class="elsevierStyleCrossRefs" href="#bib0048"><span class="elsevierStyleSup">48&#8211;50</span></a> On the other hand&#44; a substantial number of studies report that there is not an association between age and Lp&#40;a&#41; concentrations&#44; however&#44; the question of the extent to which age can influence Lp&#40;a&#41; concentrations remains uncertain&#46;<a class="elsevierStyleCrossRef" href="#bib0006"><span class="elsevierStyleSup">6</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0049"><span class="elsevierStyleSup">49</span></a></p><p id="para0044" class="elsevierStylePara elsevierViewall">In the present study&#44; there was no significant difference between the concentrations of Lp&#40;a&#41; and gender&#46; However&#44; a meta-analysis with&#160;36&#160;studies showed that females had&#160;12&#37; higher concentrations of Lp&#40;a&#41; compared to males&#46;<a class="elsevierStyleCrossRef" href="#bib0051"><span class="elsevierStyleSup">51</span></a> Likewise&#44; it occurred with the BMI&#44; where there were no significant results for the BMI classes&#44; but it was the LAP&#44; also considered a parameter of adiposity&#44; which was indirectly related to the Lp&#40;a&#41;&#46; In a Japanese study&#44; with&#160;2&#44;997&#160;asymptomatic individuals aged between&#160;40 and&#160;69&#160;years&#44; Lp&#40;a&#41; concentrations were shown lower in non-obese individuals &#40;BMI&#160;&#8805; 26&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0052"><span class="elsevierStyleSup">52</span></a></p><p id="para0045" class="elsevierStylePara elsevierViewall">The concentration of GGT in the present study was directly correlated with the concentrations of Lp&#40;a&#41;&#46; Since there is a similarity between Lp&#40;a&#41; and the LDL particle&#44; some studies propose that Lp&#40;a&#41; also undergoes an oxidative process as LDL&#44; and during the atherosclerotic process and GGT activity can increase to compensate for the increase in oxidative stimulants&#44; increasing the synthesis of glutathione&#44; which is an important antioxidant&#46;<a class="elsevierStyleCrossRef" href="#bib0001"><span class="elsevierStyleSup">1</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0053"><span class="elsevierStyleSup">53</span></a> A study conducted by Ghatge and collaborators<a class="elsevierStyleCrossRef" href="#bib0054"><span class="elsevierStyleSup">54</span></a> also found a positive correlation between the concentrations of Lp&#40;a&#41; and GGT&#46;</p><p id="para0046" class="elsevierStylePara elsevierViewall">In this study&#44; PON1 also showed a significant correlation and increased activity in individuals whose Lp&#40;a&#41; concentrations were above&#160;30&#160;mg&#47;dL&#46; This was described in a study with individuals who had moderate to high concentrations of Lp&#40;a&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">55</span></a> It is not yet clear whether PON1 concentrations may have any benefit in individuals with high concentrations of Lp&#40;a&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">55</span></a> The serum concentrations of hsCRP were also correlated to Lp&#40;a&#41;&#44; and the comparison between individuals with the presence and absence of plaques was significant by the Man Whitney test &#40;p &#60; 0&#46;02&#41;&#44; which may suggest a possible underlying inflammatory process implied by atherosclerosis&#46;<a class="elsevierStyleCrossRef" href="#bib0053"><span class="elsevierStyleSup">53</span></a></p><p id="para0047" class="elsevierStylePara elsevierViewall">The present study has certain limitations since it has not analyzed genetic factors that influence the concentration of Lp&#40;a&#41; and the identification of apo &#40;a&#41; isoforms&#46; Another limitation is that only carotid ultrasound was performed and no other arterial systems susceptible to atherosclerosis were examined&#46; Therefore&#44; the outcome could have been different or increased from the present results if the coronary and femoral arteries had been analyzed&#46; Nevertheless&#44; a strict criterion was adopted for the selection of participants&#44; which caused a limited number of individuals&#44; and the analysis of Lp&#40;a&#41; was performed by nephelometry&#44; considered the gold standard for analysis of Lp&#40;a&#41;&#46;</p><p id="para0048" class="elsevierStylePara elsevierViewall">This study pointed out that Lp&#40;a&#41; concentrations above&#160;30&#160;mg&#47;dL were associated with the presence of carotid plaques in asymptomatic individuals with a median age of&#160;43&#160;years&#44; and a 2&#37;&#160;odds ratio for the presence of plaques&#46; In fact&#44; the relationship between Lp&#40;a&#41; and CVD in general&#44; is well established in the literature&#44; however&#44; the strength of these associations and the mechanism in which Lp&#40;a&#41; influences the atherosclerotic process must be explored further&#46;</p></span></span>"
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          "titulo" => "Introduction"
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          "titulo" => "Materials and methods"
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              "titulo" => "Clinical and anthropometrical evaluation"
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              "titulo" => "Biochemical analysis"
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              "identificador" => "sec0006"
              "titulo" => "Carotid Intima-Media Thickness &#40;cIMT&#41; determination and carotid plaques detection"
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              "titulo" => "Statistical analysis"
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    "fechaRecibido" => "2022-04-22"
    "fechaAceptado" => "2022-08-29"
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          "clase" => "keyword"
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          "palabras" => array:3 [
            0 => "Lipoprotein &#40;a&#41;"
            1 => "Carotid atherosclerosis"
            2 => "Carotid plaques"
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    "highlights" => array:2 [
      "titulo" => "Highlights"
      "resumen" => "<span id="abss0001" class="elsevierStyleSection elsevierViewall"><p id="spara009" class="elsevierStyleSimplePara elsevierViewall"><ul class="elsevierStyleList" id="celist0001"><li class="elsevierStyleListItem" id="celistitem0001"><span class="elsevierStyleLabel">&#8226;</span><p id="para0001" class="elsevierStylePara elsevierViewall">High lipoprotein &#40;a&#41; levels increase the risk of carotid plaques presence in asymptomatic subjects&#46;</p></li><li class="elsevierStyleListItem" id="celistitem0002"><span class="elsevierStyleLabel">&#8226;</span><p id="para0002" class="elsevierStylePara elsevierViewall">Carotid intima-media thickness is not affected by plasma lipoprotein &#40;a&#41; levels&#46;</p></li><li class="elsevierStyleListItem" id="celistitem0003"><span class="elsevierStyleLabel">&#8226;</span><p id="para0003" class="elsevierStylePara elsevierViewall">Age and race are directly associated with lipoprotein &#40;a&#41; levels&#44; suggesting an important influence even in a highly miscegenated population&#46;</p></li></ul></p></span>"
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        "titulo" => "Abstract"
        "resumen" => "<span id="abss0003" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0003">Background</span><p id="spara010" class="elsevierStyleSimplePara elsevierViewall">This study aimed to evaluate the associations between Lipoprotein &#40;a&#41; &#8210; Lp&#40;a&#41; levels and carotid Intima-Media Thickness &#40;cIMT&#41; and with carotid plaques in healthy subjects because of previous contradictory data&#46;</p></span> <span id="abss0004" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0004">Methods</span><p id="spara011" class="elsevierStyleSimplePara elsevierViewall">A total of&#160;317&#160;healthy normolipidemic subjects &#40;20&#8210;77&#160;years old&#41; were selected&#46; The cIMT and atherosclerotic plaques were determined by B-mode ultrasonography&#46; Mann-Whitney tests were performed to compare the groups according to Lp&#40;a&#41; levels and to explore the associations between Lp&#40;a&#41;&#44; carotid plaques&#44; and cIMT&#44; logistic and linear regression analyses were performed&#46;</p></span> <span id="abss0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0005">Results</span><p id="spara012" class="elsevierStyleSimplePara elsevierViewall">Studied population &#40;51&#37;&#160;females&#44; median age&#160;43&#160;years old&#41; presented carotid plaques and cIMT&#160;&#8805; 0&#46;9&#160;mm in&#160;23&#37; and&#160;18&#37; of the participants&#44; respectively&#46; The group with Lp&#40;a&#41; levels&#160;&#62; 30&#160;mg&#47;dL presented significantly higher age and atherosclerotic plaques&#46; Indeed&#44; multivariate linear regression analysis showed a significant association between Lp&#40;a&#41;&#44; age&#44; and race&#46; On the other hand&#44; logistic regression analysis demonstrated that the subjects with Lp&#40;a&#41;&#160;&#62; 30&#160;mg&#47;dL have a significantly high risk of carotid plaques&#46;</p></span> <span id="abss0006" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0006">Conclusion</span><p id="spara013" class="elsevierStyleSimplePara elsevierViewall">The data from the present study indicate that Lp&#40;a&#41; levels above&#160;30&#160;mg&#47;dL contribute to the development of carotid plaques even in apparently healthy participants&#46;</p></span>"
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          "leyenda" => "<p id="spara002" class="elsevierStyleSimplePara elsevierViewall">N&#44; Sample size&#59; Non-whites include&#58; Blacks&#44; mixed races&#44; and asian&#59; BMI&#44; Body mass index&#59; LAP&#44; Lipid accumulation product&#59; SBP&#44; Systolic blood pressure&#59; DBP&#44; Dastolic blood pressure&#59; cIMT&#44; Carotid intima media thickness&#59; HDL-C&#44; High-density lipoprotein cholesterol&#59; NHDL-C&#44; Non-high density lipoprotein cholesterol&#59; LDL-C&#44; Low-density lipoprotein cholesterol&#59; VLDL-C&#44; Very low-density lipoprotein cholesterol&#59; ApoA-I&#44; Apolipoprotein A&#8210;I&#59; ApoB-100&#44; Apolipoprotein B100&#59; Lp&#40;a&#41;&#44; Lipoprotein &#40;a&#41;&#59; hsCRP&#44; High sensitivity C-reactive protein&#59; PON1&#44; Paraoxonase-1&#59; ALT&#44; Alanine aminotransferase&#59; AST&#44; Aspartate aminotransferase&#59; ALP&#44; Alkaline phosphatase&#59; GGT&#44; Gamma glutamyl transferase&#59; TSH&#44; Thyroid stimulating hormone&#59; FT4&#44; Free thyroxine&#46; Literature used for reference values&#58; Brazilian Guidelines on Obesity&#160;2016 4<span class="elsevierStyleSup">th</span>&#160;edition&#59; World health organization &#8210; average body mass index&#59; Brazilian Guideline for Hypertension&#59; Update of the Brazilian guideline on dyslipidemia and prevention of atherosclerosis&#160;2017&#59; Guideline of the Brazilian Diabetes Society&#59; Clinical diagnosis and treatment by laboratory methods&#160;21&#160;edition&#59; Clinical practice guideline for the assessment and management of chronic kidney disease&#59; Brazilian consensus on thyroid&#46; Values are expressed as median and interquartile range &#40;25<span class="elsevierStyleSup">th</span>&#160;and&#160;75<span class="elsevierStyleSup">th</span>&#41;&#46;</p>"
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                  \t\t\t\t</td><a name="en0008"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8210;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0009"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Sex &#40;Female&#47;Male&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0010"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">259&#47;58&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0011"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8210;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0012"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Race &#40;White&#47;Non-white&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0013"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0014"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">23 &#40;22&#8210;25&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0015"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">BMI &#40;kg&#47;m<span class="elsevierStyleSup">2</span>&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0016"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0017"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">74 &#40;68&#8210;81&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0018"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Waist circunference &#40;cm&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0019"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">316&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0020"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">92 &#40;88&#8210;98&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0021"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Hips circunference &#40;cm&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0022"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">316&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0023"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;8 &#40;0&#46;7&#8210;0&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0024"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Waist-to-hip ratio&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0025"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0026"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;5 &#40;0&#46;4&#8210;0&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0027"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Waist-to-height ratio&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0028"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0029"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">9 &#40;4&#8210;17&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0030"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">LAP &#40;cm&#47;mmoL&#47;L&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0031"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0032"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">120 &#40;110&#8210;128&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0033"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">SBP &#40;mmHg&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0034"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0035"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">80 &#40;72&#8210;80&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0036"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">DBP &#40;mmHg&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0037"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0038"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;6 &#40;0&#46;5&#8210;0&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0039"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Left cIMT &#40;mm&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0040"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0041"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;6 &#40;0&#46;5&#8210;0&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0042"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Right cIMT &#40;mm&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0043"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0044"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;6 &#40;0&#46;5&#8210;0&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0045"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Mean cIMT mm&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0046"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">58&#47;259&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0047"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8210;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0048"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Plaques &#40;Yes&#47;No&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0049"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0050"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">173 &#40;153&#8210;198&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0051"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Total cholesterol &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0052"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0053"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">58 &#40;38&#8210;74&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0054"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">HDL-C &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0055"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0056"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">117 &#40;98&#8210;135&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0057"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">NHDL-C &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0058"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0059"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">73 &#40;55&#8210;95&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0060"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Triglycerides &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0061"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0062"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">101 &#40;85&#8210;120&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0063"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">LDL-C &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0064"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0065"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">15 &#40;11&#8210;19&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0066"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">VLDL-C &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0067"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0068"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">149 &#40;118&#8210;176&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0069"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">ApoA-I &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0070"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0071"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">78 &#40;67&#8210;93&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0072"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">ApoB100 &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0073"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0074"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">12 &#40;4&#8210;26&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0075"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Lp&#40;a&#41; &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0076"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">313&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0077"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;8 &#40;0&#46;4&#8210;1&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0078"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">hsCRP &#40;mg&#47;L&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0079"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">315&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0080"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">32 &#40;13&#8210;53&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0081"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">PON1 &#40;&#181;moL&#47;min&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0082"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0083"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">84 &#40;78&#8210;88&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0084"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Glucose &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0085"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0086"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">30 &#40;25&#8210;35&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0087"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Urea &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0088"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0089"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;8 &#40;0&#46;7&#8210;0&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0090"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Creatinine &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0091"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0092"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">4&#46;5 &#40;3&#46;8&#8210;5&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0093"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Uric acid &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0094"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0095"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">17 &#40;13&#8210;22&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0096"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">ALT &#40;U&#47;L&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0097"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">297&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0098"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">19 &#40;16&#8210;23&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0099"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">AST &#40;U&#47;L&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0100"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">316&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0101"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">65 &#40;52&#8210;76&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0102"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">ALP &#40;U&#47;L&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0103"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">297&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0104"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">18 &#40;13&#8210;25&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0105"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">GGT &#40;U&#47;L&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0106"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0107"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">2 &#40;1&#46;4&#8210;2&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0108"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">TSH &#40;uUI&#47;mL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0109"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0110"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;3 &#40;1&#46;2&#8210;1&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0111"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">FT4 &#40;ng&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
              "imagenFichero" => array:1 [
                0 => "xTab3252718.png"
              ]
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spara001" class="elsevierStyleSimplePara elsevierViewall">Anthropometric&#44; clinical&#44; and biochemical characteristics of individuals&#46;</p>"
        ]
      ]
      1 => array:8 [
        "identificador" => "tbl0002"
        "etiqueta" => "Table 2"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "alt0002"
            "detalle" => "Table "
            "rol" => "short"
          ]
        ]
        "tabla" => array:2 [
          "leyenda" => "<p id="spara004" class="elsevierStyleSimplePara elsevierViewall">N&#44; Sample size&#59; Lp&#40;a&#41;&#44; Lipoprotein &#40;a&#41;&#59; Non-whites included&#44;&#58; Blacks&#44; mixed races&#44; and asian&#59; ApoB-100&#44; Apolipoprotein B100&#59; hsCRP&#44; high sensitivity&#160;C-reactive protein&#59; PON1&#44; Activity paraoxonase&#160;1&#59; GGT&#44; Gamma-glutamyltransferase&#59; Values are expressed as interquartile ranges &#40;25<span class="elsevierStyleSup">th</span> and 75<span class="elsevierStyleSup">th</span>&#41;&#59; significant p-value&#58;&#160;&#8804; 0&#46;05&#59; the numerical variables were compared by the Mann-Whitney test and the non&#8210;numerical variables by Chi-Square&#59; the variable Lp&#40;a&#41; was transformed into&#46;</p>"
          "tablatextoimagen" => array:1 [
            0 => array:2 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><a name="en0112"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="top" scope="col">Parameters&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0113"></a><th class="td-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Lp&#40;a&#41; &#8804; 30&#160;mg&#47;dL&#41;</th><a name="en0114"></a><th class="td-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Lp&#40;a&#41; &#62; 30&#160;mg&#47;dL</th><a name="en0115"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="top" scope="col">p&#8210;value&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr><tr title="table-row"><a name="en0112a"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0117"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">n&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0118"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Median &#40;25<span class="elsevierStyleSup">th</span>&#8210;75<span class="elsevierStyleSup">th</span>&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0119"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">n&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0120"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Median &#40;25<span class="elsevierStyleSup">th</span>&#8210;75<span class="elsevierStyleSup">th</span>&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0115a"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0122"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Age &#40;years&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0123"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">250&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0124"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">43 &#40;33&#8210;53&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0125"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">67&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0126"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">45 &#40;36&#8210;57&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0127"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;04</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0128"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Race &#40;White&#47;No&#8210;white&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0129"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">215&#47;35&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0130"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0131"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">44&#47;23&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0132"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0133"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;01</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0134"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Plaque &#40;Yes&#47;No&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0135"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">40&#47;210&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0136"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0137"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">18&#47;49&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0138"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0139"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;04</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0140"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="6" align="left" valign="top">Biochemical parameters</td></tr><tr title="table-row"><a name="en0141"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">ApoB100 &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0142"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">250&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0143"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">76 &#40;65&#8210;91&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0144"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">67&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0145"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">86 &#40;75&#8210;102&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0146"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">&#60; 0&#46;01</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0147"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">hsCRP &#40;mg&#47;L&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0148"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">247&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0149"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;80 &#40;0&#46;40&#8210;1&#46;50&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0150"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">66&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0151"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;93 &#40;0&#46;50&#8210;1&#46;90&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0152"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;07&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0153"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">PON1 &#40;&#181;moL&#47;min&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0154"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">249&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0155"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">28 &#40;12&#8210;52&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0156"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">66&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0157"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">42 &#40;19&#8210;57&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0158"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;01</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0159"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">GGT &#40;U&#47;L&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0160"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">236&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0161"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">17 &#40;13&#8210;23&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0162"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">61&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0163"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">21 &#40;15&#8210;30&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0164"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;02</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
              "imagenFichero" => array:1 [
                0 => "xTab3252717.png"
              ]
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spara003" class="elsevierStyleSimplePara elsevierViewall">Significant comparisons of demographic and biochemical variables of individuals by serum Lp&#40;a&#41; concentrations&#46;</p>"
        ]
      ]
      2 => array:8 [
        "identificador" => "tbl0003"
        "etiqueta" => "Table 3"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "alt0003"
            "detalle" => "Table "
            "rol" => "short"
          ]
        ]
        "tabla" => array:2 [
          "leyenda" => "<p id="spara006" class="elsevierStyleSimplePara elsevierViewall">Linear regression analysis&#59; N&#44; Number of individuals&#59; &#946;&#44; Estimated parameter&#59; significant p-value&#160;&#8804; 0&#46;05&#59; Non-whites include blacks&#44; mixed races and asian&#59; LAP&#44; Lipid accumulation product&#59; SBP&#44; Systolic blood pressure&#59; DBP&#44; Diastolic blood pressure&#46;</p>"
          "tablatextoimagen" => array:1 [
            0 => array:2 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><a name="en0165"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0166"></a><th class="td-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Univariate</th><a name="en0167"></a><th class="td-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="4" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Multivariate</th></tr><tr title="table-row"><a name="en0168"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Parameters&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0169"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">n&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0170"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&#914;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0171"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">p-value&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0172"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&#946;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0173"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">R<span class="elsevierStyleSup">2</span>-partial&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0174"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">R<span class="elsevierStyleSup">2</span>-total&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0175"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">p-value&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0176"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Age &#40;years&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0177"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0178"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;21&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0179"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">&#60; 0&#46;01</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0180"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;35&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0181"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;02</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0182"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;07</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0183"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">&#60; 0&#46;01</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0184"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Race &#40;White&#47;No-white&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0185"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0186"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">34&#46;73&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0187"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">&#60; 0&#46;01</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0188"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">32&#46;07&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0189"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;04</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0190"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0191"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;01</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0192"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">LAP &#40;cm&#47;mmoL&#47;L&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0193"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0194"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8210;0&#46;65&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0195"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;14&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0196"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">-0&#46;87&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0197"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;01</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0198"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0199"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;05</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0200"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">SBP &#40;mmHg&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0201"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0202"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;93&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0203"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;01</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0204"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0205"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0206"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0207"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0208"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">DBP &#40;mmHg&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0209"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">317&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0210"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;00&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0211"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;02</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0212"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0213"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0214"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0215"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
              "imagenFichero" => array:1 [
                0 => "xTab3252715.png"
              ]
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        ]
        "descripcion" => array:1 [
          "en" => "<p id="spara005" class="elsevierStyleSimplePara elsevierViewall">Linear regression analysis between Lp&#40;a&#41; and clinical and anthropometric parameters&#46;</p>"
        ]
      ]
      3 => array:8 [
        "identificador" => "tbl0004"
        "etiqueta" => "Table 4"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "alt0004"
            "detalle" => "Table "
            "rol" => "short"
          ]
        ]
        "tabla" => array:2 [
          "leyenda" => "<p id="spara008" class="elsevierStyleSimplePara elsevierViewall">OR&#44; Odds Ratio&#59; 95&#37;&#160;CI&#44; Confidence Interval 95&#37;&#59; Non-whites Include&#58; blacks&#44; mixed races and asian&#59; Lp&#40;a&#41;&#44; Lipoprotein &#40;a&#41;&#59; p-value &#8804; 0&#46;05&#59; Lp&#40;a&#41; was transformed into&#46;</p>"
          "tablatextoimagen" => array:1 [
            0 => array:2 [
              "tabla" => array:1 [
                0 => """
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                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><a name="en0216"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0217"></a><th class="td-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Univariate</th><a name="en0218"></a><th class="td-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Multivariate</th></tr><tr title="table-row"><a name="en0219"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Parameters&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0220"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">OR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0221"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">95&#37;&#160;CI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0222"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">p-value&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0223"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">OR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0224"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">95&#37;&#160;CI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0225"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">p-value&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0226"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Age &#40;years&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0227"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;11&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0228"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;08&#8210;1&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0229"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">&#60; 0&#46;01</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0230"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;11&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0231"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;08&#8210;1&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0232"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">&#60; 0&#46;01</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0233"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Race &#40;White&#47;No-white&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0234"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;97&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0235"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;0&#8210;3&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0236"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;05</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0237"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">2&#46;50&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0238"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;2&#8210;5&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0239"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top"><span class="elsevierStyleBold">0&#46;02</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0240"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Lp&#40;a&#41; &#40;mg&#47;dL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0241"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;02&nbsp;\t\t\t\t\t\t\n
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                        "tituloSerie" => "J Proteomics"
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                        "volumen" => "74"
                        "numero" => "12"
                        "paginaInicial" => "2881"
                        "paginaFinal" => "2891"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/21802535"
                            "web" => "Medline"
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          ]
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      ]
    ]
    "agradecimientos" => array:1 [
      0 => array:4 [
        "identificador" => "xack684958"
        "titulo" => "Acknowledgments"
        "texto" => "<p id="para0050" class="elsevierStylePara elsevierViewall">The authors acknowledge the Municipal Health Department of Campinas for furnishing the data and authorization of their use&#46; We thank Dr&#46; Jamal Baraccat from the Department of Radiology at the School of Medical Sciences&#44; State University of Campinas &#40;UNICAMP&#41;&#44; for performing the carotid measurements&#46; We thank the Statistics Department&#44; Faculty of Medical Sciences&#44; and UNICAMP for the statistical assistance&#46; This work was supported by the State of Sao Paulo Research Foundation &#40;FAPESP&#41; grant number n&#176;&#160;2006&#47;60585-9 and by Coordination for the Improvement of Higher Education Personnel &#40;CAPES&#41; &#8210; Brazil &#8211; Grant number&#160;88882&#46;434895&#47;2019-01&#46;</p>"
        "vista" => "all"
      ]
    ]
  ]
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Article information

ISSN: 18075932
Original language: English

DOI:10.1016/j.clinsp.2022.100107

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