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array:22 [ "pii" => "S0025775324004007" "issn" => "00257753" "doi" => "10.1016/j.medcli.2024.05.023" "estado" => "S200" "fechaPublicacion" => "2024-07-22" "aid" => "6730" "copyright" => "Elsevier España, S.L.U.. All rights reserved" "copyrightAnyo" => "2024" "documento" => "article" "crossmark" => 0 "subdocumento" => "fla" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "itemSiguiente" => array:17 [ "pii" => "S0025775324004019" "issn" => "00257753" "doi" => "10.1016/j.medcli.2024.05.025" "estado" => "S200" "fechaPublicacion" => "2024-07-22" "aid" => "6732" "documento" => "simple-article" "crossmark" => 0 "subdocumento" => "edi" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "es" => array:9 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Editorial</span>" "titulo" => "Insuficiencia cardíaca y fibrilación auricular" "tienePdf" => "es" "tieneTextoCompleto" => "es" "titulosAlternativos" => array:1 [ "en" => array:1 [ "titulo" => "Heart failure and atrial fibrillation" ] ] "contieneTextoCompleto" => array:1 [ "es" => true ] "contienePdf" => array:1 [ "es" => true ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Sergio Raposeiras Roubín, Nicolás López Canoa" "autores" => array:2 [ 0 => array:2 [ "nombre" => "Sergio" "apellidos" => "Raposeiras Roubín" ] 1 => array:2 [ "nombre" => "Nicolás" "apellidos" => "López Canoa" ] ] ] ] ] "idiomaDefecto" => "es" "Traduccion" => array:1 [ "en" => array:9 [ "pii" => "S2387020624005126" "doi" => "10.1016/j.medcle.2024.05.026" "estado" => "S200" "subdocumento" => "" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2387020624005126?idApp=UINPBA00004N" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0025775324004019?idApp=UINPBA00004N" "url" => "/00257753/unassign/S0025775324004019/v1_202407220410/es/main.assets" ] "itemAnterior" => array:16 [ "pii" => "S0025775312001376" "issn" => "00257753" "doi" => "10.1016/j.medcli.2012.01.024" "estado" => "S200" "fechaPublicacion" => "2013-05-02" "aid" => "2089" "documento" => "simple-article" "crossmark" => 0 "subdocumento" => "dup" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:2 [ "total" => 9 "PDF" => 9 ] "es" => array:8 [ "idiomaDefecto" => true "titulo" => "WITHDRAWN: Prevalencia y factores asociados a infección por <span class="elsevierStyleItalic">Chlamydia trachomatis</span> en reclusos jóvenes de Cataluña" "tienePdf" => "es" "tieneTextoCompleto" => 0 "tieneResumen" => "es" "contieneResumen" => array:1 [ "es" => true ] "contienePdf" => array:1 [ "es" => true ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Evelin López Corbeto, Dolors Carnicer-Pont, Rossie Lugo, Victoria Gonzalez, Elisabeth Bascuñana, Nuria Lleopart, Luis Barbero, Victoria Humet, Jordi Casabona" "autores" => array:10 [ 0 => array:2 [ "nombre" => "Evelin" "apellidos" => "López Corbeto" ] 1 => array:2 [ "nombre" => "Dolors" "apellidos" => "Carnicer-Pont" ] 2 => array:2 [ "nombre" => "Rossie" "apellidos" => "Lugo" ] 3 => array:2 [ "nombre" => "Victoria" "apellidos" => "Gonzalez" ] 4 => array:2 [ "nombre" => "Elisabeth" "apellidos" => "Bascuñana" ] 5 => array:2 [ "nombre" => "Nuria" "apellidos" => "Lleopart" ] 6 => array:2 [ "nombre" => "Luis" "apellidos" => "Barbero" ] 7 => array:2 [ "nombre" => "Victoria" "apellidos" => "Humet" ] 8 => array:2 [ "nombre" => "Jordi" "apellidos" => "Casabona" ] 9 => array:1 [ "colaborador" => "Grupo de Estudio CT Prisiones" ] ] ] ] ] "idiomaDefecto" => "es" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0025775312001376?idApp=UINPBA00004N" "url" => "/00257753/unassign/S0025775312001376/v1_201305021159/es/main.assets" ] "en" => array:18 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "Temporal variability of Lp(a) in clinically stable patients: Implications for cardiovascular risk assessment" "tieneTextoCompleto" => true "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Maria G. Matta, Laura Schreier, Augusto Lavalle-Cobo, Sebastian Garcia-Zamora, Agustina Ferraresi, Angeles Madsen, Sofia Bellini, Guadalupe Ramos, Paula Roubicek, Pablo Corral" "autores" => array:10 [ 0 => array:4 [ "nombre" => "Maria G." "apellidos" => "Matta" "email" => array:1 [ 0 => "magabrielama@gmail.com" ] "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] 2 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "Laura" "apellidos" => "Schreier" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] 2 => array:3 [ "nombre" => "Augusto" "apellidos" => "Lavalle-Cobo" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "aff0020" ] ] ] 3 => array:3 [ "nombre" => "Sebastian" "apellidos" => "Garcia-Zamora" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">e</span>" "identificador" => "aff0025" ] ] ] 4 => array:3 [ "nombre" => "Agustina" "apellidos" => "Ferraresi" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 5 => array:3 [ "nombre" => "Angeles" "apellidos" => "Madsen" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 6 => array:3 [ "nombre" => "Sofia" "apellidos" => "Bellini" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 7 => array:3 [ "nombre" => "Guadalupe" "apellidos" => "Ramos" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 8 => array:3 [ "nombre" => "Paula" "apellidos" => "Roubicek" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 9 => array:3 [ "nombre" => "Pablo" "apellidos" => "Corral" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] ] "afiliaciones" => array:5 [ 0 => array:3 [ "entidad" => "Department of Pharmacology, Faculty of Medicine, Universidad FASTA, Clinical Researcher at the Clinical Research Institute (IIC), Mar del Plata, Argentina" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Cardiology Department, Townsville University Hospital, 100 Angus Smith Dr, Douglas QLD 4814, Australia" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "University of Buenos Aires, Faculty of Pharmacy and Biochemistry, Department of Clinical Biochemistry, Lipids and Atherosclerosis Laboratory, INFIBIOC-UBA, Argentina" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Cardiology Department, Sanatorio Otamendi, CABA, Argentina" "etiqueta" => "d" "identificador" => "aff0020" ] 4 => array:3 [ "entidad" => "Sanatorio Delta, Rosario, Argentina" "etiqueta" => "e" "identificador" => "aff0025" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Variabilidad temporal de Lp(a) en pacientes clínicamente estables: implicaciones para la evaluación del riesgo cardiovascular" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1712 "Ancho" => 3333 "Tamanyo" => 447184 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Graph of temporal variability of Lp(a) in nmol/L for each patient. This figure demonstrates the temporal variability of Lp(a) levels among 61 participants across 171 separate determinations, over a monitoring period that spanned from a minimum of 4 months to a maximum of 48 months. The <span class="elsevierStyleItalic">x</span>-axis represents sequential measurements, indicating the time points at which Lp(a) levels were assessed for each patient. The <span class="elsevierStyleItalic">y</span>-axis quantifies the Lp(a) concentration in nanomoles per liter (nmol/L. Individual patient trajectories are plotted to exhibit the variation in Lp(a) levels over time.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Lipoprotein(a) [Lp(a)], a unique LDL particle with the additional apolipoprotein(a) [apo(a)], is increasingly recognized as a critical and independent risk factor for cardiovascular diseases (CVD) including myocardial infarction, stroke, and aortic valve calcification.<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">1</span></a> Despite its significant role in CVD, the routine clinical assessment of Lp(a) is often overlooked, and there are no specific treatments targeting its reduction. This underscores the urgent need for a deeper understanding of Lp(a)’s role in CVD management and prevention.<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">2</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Traditionally, Lp(a) levels have been considered stable and predominantly genetically determined, leading to the general recommendation of a single lifetime measurement.<a class="elsevierStyleCrossRefs" href="#bib0120"><span class="elsevierStyleSup">3–5</span></a> However, emerging evidence challenges this notion.<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">6</span></a> The study by De Boer et al. provides insight into the variability of Lp(a) levels from childhood to adulthood, suggesting that changes can occur at different life stages.<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">7</span></a> Alongside, studies like the ARIC study have observed significant reclassification in Lp(a) levels upon repeated measurements,<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">8</span></a> and clinical trials involving interventional drugs like pelacarsen and olpasiran have shown fluctuations in Lp(a) levels, particularly in patients with initially high concentrations.<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">9</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">These observations, coupled with the influence of clinical conditions such as menopause, chronic kidney disease, and the use of medications like statins and PCSK9 inhibitors, suggest a more complex and dynamic behavior of Lp(a) levels than previously understood.<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">10</span></a> This variability could have profound implications for cardiovascular risk assessment and management in clinical practice.</p><p id="par0020" class="elsevierStylePara elsevierViewall">This study aims to comprehensively evaluate the potential variability of Lp(a) over time in clinically stable patients. We categorized Lp(a) levels into normal, borderline, and elevated categories, with a secondary objective of exploring the underlying reasons for significant variability, particularly in patients with hypervariable Lp(a) levels.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Materials and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Study population and data collection</span><p id="par0025" class="elsevierStylePara elsevierViewall">A retrospective analysis was conducted on a registry of patients who attended a Lipid Clinic from February 2018 to December 2022. To be included in the analysis, patients had to demonstrate stable clinical status and had to have at least two Lp(a) measurements taken with a minimum interval of four months. This period was empirically considered due to a lack of evidence regarding the measurement intervals. A follow-up was conducted with repeated determination of Lp(a) in a group of patients, consecutively, regardless of their initial value and status (primary or secondary prevention). The baseline measurement and the subsequent determination with the highest positive or negative difference were considered for assessing variability. The study protocol received approval from FFyB-UBA (Res CD1762/17), guaranteeing the preservation of privacy and anonymity.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Lp(a) assessment and classification</span><p id="par0030" class="elsevierStylePara elsevierViewall">Lp(a) measurements were consistently performed in the same laboratory, and using the same methodology: Immunoturbidimetric assay, utilizing polyclonal antibodies against human Lp(a) and reference material traceable to SRM2B IFCC/WHO, independent of the apo(a) size (LPA2, Tina Quant lipoprotein(a)-Gen2, Roche). Analytical intra- and inter-assay coefficients of variation (CV%) were 3.2% and 4.5% respectively. Lp(a) values were expressed in nmol/L. A value below 70<span class="elsevierStyleHsp" style=""></span>nmol/L was considered normal, 70–125<span class="elsevierStyleHsp" style=""></span>nmol/L as borderline, and greater than 125<span class="elsevierStyleHsp" style=""></span>nmol/L as elevated.<a class="elsevierStyleCrossRefs" href="#bib0120"><span class="elsevierStyleSup">3,11</span></a> Variability in Lp(a) values was estimated by calculating the relative change as a percentage between the baseline value and the measurement with the greatest discrepancy.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Definitions of other variables</span><p id="par0035" class="elsevierStylePara elsevierViewall">Various medical conditions and risk factors were assessed using a combination of medical and laboratory records. These included hypertension, diabetes, smoking status, coronary artery disease, stroke, vascular disease, history of hypothyroidism or hyperthyroidism, and menopause. Smoking status was categorized into two groups: current smokers and nonsmokers. Current smokers were defined as individuals who had smoked more than 100 cigarettes throughout their lifetime and were currently smoking. Nonsmokers comprised individuals who had never smoked or had smoked fewer than 100 cigarettes in their lifetime, including ex-smokers.</p><p id="par0040" class="elsevierStylePara elsevierViewall">Body mass index (BMI) was calculated as the ratio of body weight (in kilograms) to height (in meters) squared (kg/m<span class="elsevierStyleSup">2</span>). Additionally, lipid analyses were conducted, including measurements of serum triglyceride levels after an overnight fasting period, as well as total cholesterol, LDL cholesterol (LDL-C), and glomerular filtration rate (eGFR) calculated with Cockcroft–Gault formula. The use of lipid-lowering medications was also recorded.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Statistical analysis</span><p id="par0045" class="elsevierStylePara elsevierViewall">The categorical data were presented as percentages, while continuous data were summarized using mean and standard deviation for normally distributed data. For non-normally distributed data, median and interquartile ranges were employed. The Chi-square test was utilized for categorical variables, and Fisher's exact test was employed when necessary. Student's <span class="elsevierStyleItalic">t</span>-test was applied to normally distributed numerical variables, whereas the Wilcoxon rank-sum test was used for skewed numerical variables.</p><p id="par0050" class="elsevierStylePara elsevierViewall">The variability between baseline levels and the levels with the maximum variability was analyzed both globally and within the aforementioned three categories. The correlation between baseline values and maximum variability values was assessed using Spearman's test. For the analysis of Lp(a) value variation between baseline and the point of maximum variability among the groups, the Kruskal–Wallis test was employed.</p><p id="par0055" class="elsevierStylePara elsevierViewall">Participants with a variation in the second measurement exceeding an absolute value<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>≥25% from baseline were identified as having hypervariable Lp(a) levels, and their clinical characteristics and potential influential factors were evaluated. This definition was taken from Marcovina et al.,<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">9</span></a> as it would be clinically relevant and unlikely to be a measurement method error. A multiple logistic regression model was developed manually to explore the variables associated with having hypervariable Lp(a) levels. All variables that achieved a value of <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>0.20 in the univariate model were included in the multiple logistic regression model with backward elimination to identify the independent predictors of hypervariable patients. A <span class="elsevierStyleItalic">p</span>-value of less than 0.05 was deemed statistically significant for all analyses. The statistical analysis was performed using Stata version 11.0 software (StataCorp. Stata Statistical Software: Release 11. College Station, TX: StataCorp LP; 2009).</p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Results</span><p id="par0060" class="elsevierStylePara elsevierViewall">A total of 740 patients, all of the same ethnicity (Caucasians), were analyzed, with 61 patients included in the study who had at least two Lp(a) measurements. The mean age was 59.6<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>13.0 years, with 23 (37.7%) female and 38 (62.3%) male. Overall, the population showed a higher tendency toward overweight and hypercholesterolemia with mildly elevated baseline Lp(a) values. Less than 20% had a history of CVD and the majority were being treated with statins. Baseline characteristics are presented in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>.<ul class="elsevierStyleList" id="lis0005"><li class="elsevierStyleListItem" id="lsti0005"><span class="elsevierStyleLabel">1.</span><p id="par0065" class="elsevierStylePara elsevierViewall">Lp(a) analysis</p></li></ul></p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0070" class="elsevierStylePara elsevierViewall">We analyzed a total of 171 determinations among the 61 participants. Thirty-four participants had 2 determinations, thirteen had 3, eight had 4, five had 5, and one had up to 7. The minimum period between Lp(a) measurements was 4 months, and the maximum was 48 months (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). The values of Lp(a), their variations, and correlations in categories are presented in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>. The difference between the baseline Lp(a) value and the sample with maximum variation was significant among the three groups (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05).</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall">We found 21 out of 61 participants (34.4%) with a variability ≥25%. Men in our study showed a slight tendency toward greater variability than women (15/38, 39.5% versus 6/23, 26.1%) with a non-significant <span class="elsevierStyleItalic">p</span>-value of 0.28. Within the category of Lp(a) less than 70<span class="elsevierStyleHsp" style=""></span>nmol/L, only 5 (23.8.%) had hypervariable levels, with borderline Lp(a) levels 6 (28.6%) and with high Lp(a) levels 10 (47.6%).</p><p id="par0080" class="elsevierStylePara elsevierViewall">We observed various patterns in the category changes of the participants with hypervariable Lp(a) levels. In the lowest category (Lp(a)<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>70<span class="elsevierStyleHsp" style=""></span>nmol/L), two patients transitioned to a higher category (70–125<span class="elsevierStyleHsp" style=""></span>nmol/L). In the borderline category (Lp(a) 70–125<span class="elsevierStyleHsp" style=""></span>nmol/L), two participants progressed to the highest category (>125<span class="elsevierStyleHsp" style=""></span>nmol/L), while one moved to the lowest category. Finally, among the ten patients who had hypervariable levels in the highest category, only two moved to the borderline values (Lp(a) 70–125<span class="elsevierStyleHsp" style=""></span>nmol/L) (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>).</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0085" class="elsevierStylePara elsevierViewall">After analyzing the potential causes of these variations, we discovered that participants who transitioned from the borderline to the higher category may have done so due to one participant starting statin treatment, while the other participant discontinued the PCSK9 inhibitor. No other statin changes were identified in the remaining patients who had more than two measurements. Furthermore, we could not pinpoint any other reasons for the remaining variations. Lastly, when assessing the clinical characteristics of these hypervariable patients, menopause was the factor most strongly associated with being part of this group in the univariate analysis, all the women with hypervariable Lp(a) levels were in menopause (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). In the multivariable analysis, we did not find any statistically significant variables.</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Discussion</span><p id="par0090" class="elsevierStylePara elsevierViewall">Lp(a) is a primarily genetically determined lipoprotein without a proven intervention to lower its level. Therefore, the consensus recommendation is to assess its level once in a person's lifetime. However, evidence suggests that the level of Lp(a) may vary across different populations, ages, and conditions.<a class="elsevierStyleCrossRefs" href="#bib0135"><span class="elsevierStyleSup">6–9</span></a> In our study, we aimed to evaluate the variability of lipoprotein(a) [Lp(a)] over time in a population of clinically stable patients. When we examined the correlation between baseline and subsequent measurements with the greatest discrepancy, we observed a strong correlation (Spearman rho<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.92), consistent with previous studies. For instance, Trinder et al., who analyzed Lp(a) concentrations in 16,017 unrelated individuals from the UK Biobank, found a high and stable correlation (Spearman rho<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.96; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001) between baseline and follow-up levels after 4.42 years.<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">3</span></a> Moreover, in the same study, a minimal temporal variation in Lp(a) levels was reported; 8.66% of individuals had a follow-up Lp(a) measurement at least 25<span class="elsevierStyleHsp" style=""></span>nmol/L greater than their baseline, while merely 4.12% of individuals had a measurement at least 25<span class="elsevierStyleHsp" style=""></span>nmol/L less than their baseline. Interestingly, we encountered contradictory results when analyzing the levels within three categories. The correlation was poor (Spearman rho<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.41) in the group with borderline values (Lp(a) 70–125<span class="elsevierStyleHsp" style=""></span>nmol/L), where we observed more than half of the individuals with variable Lp(a) values. In contrast, it was higher in the other two categories (rho<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.85).</p><p id="par0095" class="elsevierStylePara elsevierViewall">Accurate determination of Lp(a) levels has a significant difficulty due to the complexity of the particle. In its structure, it contains an LDL particle bound to apo(a), and the latter shows significant heterogeneity of isoforms of various sizes resulting from mutations in the LPA gene. These mutations ultimately determine the circulating levels of this lipoprotein.<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">12</span></a> The size polymorphism of apo(a) is determined by the number of repetitions of Kringles IV type 2 of the apo(a). Therefore, to achieve reliable results, it is essential to employ a validated and standardized method. It should be noted that the determination of Lp(a) in this study was performed using an internationally recommended standardized method. This method is unaffected by particle size variations, practically not influenced by lipoprotein size isoforms, and standardized with the reference materials of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC).<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">13</span></a> In addition, the expression of the results in nmol/L renders them independent of the mass (mg/dL), which can be affected by the concentration of the different components of the particle.</p><p id="par0100" class="elsevierStylePara elsevierViewall">Furthermore, it is important to consider the interpretation and reporting of variability in Lp(a) measurements, as different studies employed various metrics such as absolute numbers, mean percentages variations, or Coefficient of Variation.<a class="elsevierStyleCrossRefs" href="#bib0120"><span class="elsevierStyleSup">3,9,14–17</span></a> These discrepancies in the reported expression metrics <span class="elsevierStyleItalic">(o forms)</span> hinder comparisons and general conclusions. In our research, we focused on two measurements per person, and we observed that, as expected, our overall Lp(a) values did not follow a normal distribution. To assess intraindividual variation, we analyzed absolute and percentage changes from the baseline value using the reasoning provided by Marcovina et al.<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">9</span></a> However, they considered individuals with a change in Lp(a)<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>25%, either greater or lesser, from the mean value of their measurements as outliers. Our findings revealed that approximately one-third of the participants exhibited variability of 25% or higher. This aligns with the observations made by Marcovina et al., who reported 40.4% outliers in their study. Interestingly, these changes occurred in diverse directions, with the majority of patients (60%) experiencing increases in Lp(a) values, while 10% of patients normalized their values (from borderline 80–88<span class="elsevierStyleHsp" style=""></span>nmol/L to <75<span class="elsevierStyleHsp" style=""></span>nmol/L). Similarly, in our research, almost 80% of the cases showed increased values. When we analyzed the changes within the defined categories (<70<span class="elsevierStyleHsp" style=""></span>nmol/L, 70–125<span class="elsevierStyleHsp" style=""></span>nmol/L, or >125<span class="elsevierStyleHsp" style=""></span>nmol/L), only one individual transitioned from normal to borderline values, and two in the borderline group normalized their values. Most individuals who increased their Lp(a) values were in the borderline and highest groups. Our findings support Marcovina's group observation that most of the variability occurs in the borderline or higher value groups and question Trinder et al., who found some differences only in individuals with very low or very high values.<a class="elsevierStyleCrossRefs" href="#bib0120"><span class="elsevierStyleSup">3,9</span></a></p><p id="par0105" class="elsevierStylePara elsevierViewall">Regarding gender differences, Marcovina observed a predominance of variability in females in the group of patients with Lp(a)<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>75<span class="elsevierStyleHsp" style=""></span>nmol/L.<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">9</span></a> However, our analysis indicated that men tended to exhibit slightly higher variability than women, although this difference was not statistically significant. On the other hand, when we assessed clinical characteristics of the patients with hypervariable levels, we found that menopause had a significant association with being part of this group in the univariate analysis. This aligns with previous knowledge suggesting that estrogen and anabolic steroids suppress apo(a) synthesis, explaining the post-menopausal increase in Lp(a) levels.<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">18</span></a></p><p id="par0110" class="elsevierStylePara elsevierViewall">Our findings on Lp(a) variability in clinically stable patients, aligning with studies like OCEAN(a)-DOSE by Gaba et al.,<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">19</span></a> highlight the dynamic nature of Lp(a) levels and the necessity of multiple measurements for precise cardiovascular risk assessment. This concept is further complicated by the impact of statin therapy, as indicated by our observation of hypervariability and supported by Trinder et al., suggesting statin-specific effects on Lp(a) levels.<a class="elsevierStyleCrossRefs" href="#bib0120"><span class="elsevierStyleSup">3,20,21</span></a> Furthermore, emerging research underscores the significance of Lp(a) variability in predicting poor cardiovascular outcomes, particularly in individuals with Familial Hypercholesterolemia.<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">15</span></a> This is complemented by findings linking Lp(a) variability with elevated CRP levels, as seen in a study involving 2712 patients, where higher Lp(a) variability correlated with increased inflammatory status.<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">16</span></a> Together, these insights emphasize the multifaceted nature of Lp(a) in cardiovascular risk management and prognosis.</p><p id="par0115" class="elsevierStylePara elsevierViewall">The present study has some limitations that should be acknowledged. Firstly, the data exclusively come from a single lipid clinic, which may limit the generalizability of the findings to other populations. This suggests that the average level of Lp(a) observed might be higher than in the general population, potentially introducing a selection bias toward patients with baseline Lp(a) values<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>125<span class="elsevierStyleHsp" style=""></span>nmol/L. Additionally, the relatively small sample size could reduce statistical power and the ability to detect significant associations. Another factor that might have contributed to the variability is regression to the mean. However, this phenomenon is more pronounced in the extreme values of a sample, and we predominantly observed it in those with the lowest values. Nonetheless, we can speculate that regression to the mean should occur in all patients, not just in a subgroup of participants. Finally, the variability of Lp(a) levels did not change significantly between the first and second measurements. However, for patients with three or more measurements, the variability seems to be higher. This indicates that the follow-up period of the study might be too short for most patients, and a study with a longer follow-up time could provide more conclusive results on the long-term variability of Lp(a).</p><p id="par0120" class="elsevierStylePara elsevierViewall">Despite these limitations, the study has strong points. The recommended standardized methods for measuring Lp(a) were used, and most of the factors that could contribute to the variability of Lp(a) levels were analyzed. Finally, we collected data from patients in real-life clinical settings. The limited availability of previous research in this area makes our study even more important as it adds valuable new information to what we already know about Lp(a) variability.</p><p id="par0125" class="elsevierStylePara elsevierViewall">Our study suggests reconsidering the reliance on a single Lp(a) measurement for assessing cardiovascular risk. Repeat measurements, particularly in borderline cases, may be beneficial. However, it is paramount to underscore the necessity for additional research to fully substantiate this approach and identify contributing factors to these fluctuations.</p></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Ethical approval</span><p id="par0130" class="elsevierStylePara elsevierViewall">Our study was approved by FFyB-UBA (Res CD1762/17).</p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Funding source</span><p id="par0135" class="elsevierStylePara elsevierViewall">The present study has not received any grants or financial support.</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Authors’ contributions</span><p id="par0140" class="elsevierStylePara elsevierViewall">Conceptualization: Corral P., Schreier L., Matta M.G., Lavalle-Cobo A.</p><p id="par0145" class="elsevierStylePara elsevierViewall">Data curation: Corral P., Bellini S., Madsen A., Ferraresi A., Roubicek P., Ramos G.</p><p id="par0150" class="elsevierStylePara elsevierViewall">Formal analysis: Matta M.G., Corral P.</p><p id="par0155" class="elsevierStylePara elsevierViewall">Writing – original draft: Matta M.G.</p><p id="par0160" class="elsevierStylePara elsevierViewall">Writing – review & editing: Corral P., Schreier L., Lavalle-Cobo A., Garcia-Zamora S.</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Conflict of interest</span><p id="par0165" class="elsevierStylePara elsevierViewall">Nothing to declare.</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Data availability</span><p id="par0170" class="elsevierStylePara elsevierViewall">In accordance with our commitment to transparency, all research data is readily accessible to the public.</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Use of AI and AI-assisted technologies statement</span><p id="par0175" class="elsevierStylePara elsevierViewall">AI has not been used.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:15 [ 0 => array:3 [ "identificador" => "xres2206340" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objectives" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1850960" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres2206339" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivos" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1850959" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Materials and methods" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Study population and data collection" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Lp(a) assessment and classification" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Definitions of other variables" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Statistical analysis" ] ] ] 6 => array:2 [ "identificador" => "sec0035" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0040" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0045" "titulo" => "Ethical approval" ] 9 => array:2 [ "identificador" => "sec0050" "titulo" => "Funding source" ] 10 => array:2 [ "identificador" => "sec0055" "titulo" => "Authors’ contributions" ] 11 => array:2 [ "identificador" => "sec0060" "titulo" => "Conflict of interest" ] 12 => array:2 [ "identificador" => "sec0065" "titulo" => "Data availability" ] 13 => array:2 [ "identificador" => "sec0070" "titulo" => "Use of AI and AI-assisted technologies statement" ] 14 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2024-01-18" "fechaAceptado" => "2024-05-16" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1850960" "palabras" => array:3 [ 0 => "Lipoprotein(a)" 1 => "Cardiovascular diseases" 2 => "Cardiovascular risk factor" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1850959" "palabras" => array:3 [ 0 => "Lipoproteína(a)" 1 => "Enfermedades cardiovasculares" 2 => "Factor de riesgo cardiovascular" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objectives</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Lipoprotein(a) [Lp(a)] is a significant risk factor for cardiovascular disease, yet it is often overlooked in routine clinical assessments. As a primarily genetically determined risk factor, the traditional recommendation is to assess its level once in a lifetime, as the variability of Lp(a) over time is considered to be minimal. This study aims to evaluate the potential variability of Lp(a) in clinically stable patients and investigate factors contributing to the lack of stable levels.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">A retrospective analysis was conducted on a sample of adult patients attending a lipid clinic. Participants with at least two Lp(a) measurements taken with a minimum interval of four months were included. Lp(a) measurements were performed using the immunoturbidimetric assay. Variability in Lp(a) values was calculated as a percentage change from baseline, with participants exceeding a 25% change classified as having hypervariable Lp(a) levels. Additional clinical and biochemical variables were assessed.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">61 participants with 171 Lp(a) determinations were included. Thirty-four percent exhibited a variability of 25% or higher (hypervariable). Men showed slightly greater variability than women. Changes in Lp(a) categories were observed among hypervariable patients, with some participants experiencing an increase while others showed a decrease. Menopause was present in all the women with hypervariable levels.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Our study suggests reconsidering the reliance on a single Lp(a) measurement for assessing cardiovascular risk. Repeat measurements, particularly in borderline cases, may be beneficial.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objectives" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivos</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">La lipoproteína(a) [Lp(a)] es un factor de riesgo cardiovascular cuyo valor se considera estable a lo largo del tiempo debido a que su concentración está determinada, principalmente en forma genética. Este estudio tuvo como objetivo investigar si existe variabilidad a lo largo el tiempo en pacientes clínicamente estables y analizar los factores que contribuyen a su variabilidad.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Métodos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Análisis retrospectivo en una muestra de 61 pacientes adultos de la misma etnia que asistieron a una Clínica de Lípidos. Se incluyeron participantes con al menos dos mediciones de Lp(a) tomadas con un intervalo mínimo de cuatro meses. La Lp(a) se analizó con ensayo inmunoturbidimétrico, en un mismo laboratorio. La variabilidad en los valores de Lp(a) se calculó como un cambio porcentual desde el valor inicial, clasificando a los participantes que excedieron un cambio del 25% como hipervariables. También se evaluaron variables clínicas y bioquímicas adicionales.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Se incluyeron 61 participantes con 171 determinaciones de Lp(a). El 34% mostró una variabilidad del 25% o mayor. Los hombres mostraron una variabilidad ligeramente mayor que las mujeres. Se observaron cambios en las categorías de Lp(a) entre los hipervariables, algunos participantes experimentaron un aumento mientras que otros mostraron una disminución. La menopausia estaba presente en todos los casos de mujeres hipervariables.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusión</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Nuestra investigación sugiere replantear el uso exclusivo de una sola medición de Lp(a) para evaluar el riesgo cardiovascular. La realización de mediciones repetidas, especialmente en casos limítrofes, podría ser beneficiosa.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivos" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] ] "multimedia" => array:5 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1712 "Ancho" => 3333 "Tamanyo" => 447184 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Graph of temporal variability of Lp(a) in nmol/L for each patient. This figure demonstrates the temporal variability of Lp(a) levels among 61 participants across 171 separate determinations, over a monitoring period that spanned from a minimum of 4 months to a maximum of 48 months. The <span class="elsevierStyleItalic">x</span>-axis represents sequential measurements, indicating the time points at which Lp(a) levels were assessed for each patient. The <span class="elsevierStyleItalic">y</span>-axis quantifies the Lp(a) concentration in nanomoles per liter (nmol/L. Individual patient trajectories are plotted to exhibit the variation in Lp(a) levels over time.</p>" ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1879 "Ancho" => 3333 "Tamanyo" => 342469 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Overview of the research's findings. This figure illustrates the variability in Lp(a) levels among a subset of 740 individuals, with 61 of them undergoing repeated measurements, totaling 171 determinations. The analysis includes patients with various measurement frequencies: thirty-four participants underwent two determinations, thirteen had three, eight had four, five had five, and one individual's Lp(a) levels were measured seven times. The graph depicts transitions among three Lp(a) categories: <70<span class="elsevierStyleHsp" style=""></span>nmol/L, 70–125<span class="elsevierStyleHsp" style=""></span>nmol/L, and >125<span class="elsevierStyleHsp" style=""></span>nmol/L. Notable transitions include two patients rising from the lowest to the middle category, transitions both to and from the middle category, and two patients moving from the highest to the middle category.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">SD, standard deviation; IQR, interquartile range; LDL-C, low-density lipoprotein cholesterol; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate. Coronary heart disease: history of angina, infarct, positive ischemia test, CT angiography, or catheterization showing coronary atherosclerotic disease. Vascular disease: symptoms of intermittent claudication or Doppler ultrasound showing ≥75% obstruction of the arterial cross-sectional area, presence of a plaque, or angiography indicating ≥50% diameter obstruction or ≥75% arterial cross-sectional area obstruction. Treatment includes bypass surgery, angioplasty, or thrombolysis for peripheral vascular disease.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Characteristics \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Value \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Age – years, mean (SD)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">59.6 (13) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Sex – female, n (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23 (37.70) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Body mass index kg/m</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">2</span></span><span class="elsevierStyleItalic">, mean (SD)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27.82 (4.96) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Total cholesterol – mg/dL, mean (SD)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">207.32 (52.37) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Lipoprotein(a) – nmol/L, median (IQR)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">150 (72–226) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">LDL-C – mg/dL, mean (SD)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">125.63 (44.63) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Triglycerides – mg/dL, median (IQR)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">102 (70–147) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">CKD (eGFR</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic"><</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">60</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">ml/min/1.73</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">m</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">2</span></span><span class="elsevierStyleItalic">), n (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (3.27) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Cholesterol-lowering medication, n (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">49 (83.05) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Statins \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41 (67.2) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Ezetimibe \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (16.4) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>PCSK9i \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (1.63) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Hypothyroidism, n (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 (19.67) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Hypertension, n (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15 (24.60) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Diabetes mellitus, n (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (6.56) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Current smoker, n (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">18 (29.51) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Coronary heart disease, n (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9 (15.25) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Vascular disease, n (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (6.67) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3599924.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Participants baseline characteristics.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">IQR: interquartile range.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Characteristics \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Total<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>61 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Lp(a)<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>70<span class="elsevierStyleHsp" style=""></span>nmo/L(<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>13) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Lp(a) 70–125<span class="elsevierStyleHsp" style=""></span>nmol/L(<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>11) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Lp(a)<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>125<span class="elsevierStyleHsp" style=""></span>nmol/L(<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>37) \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Baseline Lp(a) (nmol/L), median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">150 (72–226.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 (13–51) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">88 (72–106) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">212 (172–259) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Second Lp(a) (nmol/L) with maximum discrepancy, median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">177 (80.75–226.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27 (16–56) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">94 (81–133) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">216 (181–269) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Spearman correlation between baseline and second Lp(a) value \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.9235 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.8504 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.4188 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.8584 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Absolute mean change in Lp(a), median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 (10–49) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (1–11) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">21 (13–54) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28 (16–51) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3599922.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Baseline Lp(a) values, maximum variation, correlation, and their absolute and percentage variability.</p>" ] ] 4 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at3" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">SD, standard deviation; IQR, interquartile range; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Characteristics \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">With hypervariability<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">21</span></a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Without hypervariability<span class="elsevierStyleSup">40</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span>-Value<a class="elsevierStyleCrossRef" href="#tblfn0005">*</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age – years, mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">59.6 (12.03) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">59.53 (13.63) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.99 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Sex - female, <span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (28.57) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17 (42.50) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.28 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Obesity, <span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (33.33) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (25) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.345 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Lipoprotein (a) – nmol/L, median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">106 (70–172) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">184.5 (91.5–228.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.16 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Triglycerides mg/dL, median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">110 (70–159) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">105 (69.5–129) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.25 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CKD (eGFR<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>60<span class="elsevierStyleHsp" style=""></span>ml/min/1.73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span>), <span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (4.76) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1(2.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.00 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Cholesterol-lowering medication, <span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (9.52) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.00 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hypothyroidism, <span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 (57.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (15) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.20 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hypertension, <span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (33.33) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (20.51) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.27 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Diabetes mellitus, <span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (9.52) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.49 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Current smoker, <span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (28.57) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 (30) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.90 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Menopause women (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>16), <span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (62.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.13 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3599923.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "*" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Univariate analyses (Chi-square, Wilcoxon rank-sum, or Student's <span class="elsevierStyleItalic">t</span>-test).</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Factors associated with variability in Lp(a) levels compared between patients with or without hypervariable Lp(a) levels.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:21 [ 0 => array:3 [ "identificador" => "bib0110" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Lipoprotein(a) in atherosclerotic cardiovascular disease and aortic stenosis: a European Atherosclerosis Society consensus statement" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "F. Kronenberg" 1 => "S. Mora" 2 => "E.S.G. Stroes" 3 => "B.A. Ference" 4 => "B.J. Arsenault" 5 => "L. Berglund" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1093/eurheartj/ehac361" "Revista" => array:6 [ "tituloSerie" => "Eur Heart J" "fecha" => "2022" "volumen" => "43" "paginaInicial" => "3925" "paginaFinal" => "3946" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/36036785" "web" => "Medline" ] ] ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0115" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Lipoprotein(a) as a cardiovascular risk factor: current status" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "B.G. Nordestgaard" 1 => "M.J. Chapman" 2 => "K. Ray" 3 => "J. Boren" 4 => "F. Andreotti" 5 => "G.F. 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