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"documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Med Clin. 2024;162:417-24" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "es" => array:13 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original</span>" "titulo" => "Evolución de la prevalencia de consumo de tabaco en España y sus 17 comunidades autónomas (1987-2020)" "tienePdf" => "es" "tieneTextoCompleto" => "es" "tieneResumen" => array:2 [ 0 => "es" 1 => "en" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "417" "paginaFinal" => "424" ] ] "titulosAlternativos" => array:1 [ "en" => array:1 [ "titulo" => "Evolution of smoking prevalence in Spain and its 17 autonomous regions (1987-2020)" ] ] "contieneResumen" => array:2 [ "es" => true "en" => true ] "contieneTextoCompleto" => array:1 [ "es" => true ] "contienePdf" => array:1 [ "es" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figura 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 2064 "Ancho" => 2925 "Tamanyo" => 265137 ] ] "descripcion" => array:1 [ "es" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Tendencia de las prevalencias brutas (primer panel) y estandarizadas por edad (segundo panel) de consumo de tabaco en los varones y en las mujeres en España. Periodo 1987-2020.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Julia Rey-Brandariz, Alberto Ruano-Ravina, María Isolina Santiago-Pérez, Leonor Varela-Lema, Carla Guerra-Tort, Agustín Montes, María Piñeiro, Carlos Rábade, Mónica Pérez-Ríos" "autores" => array:9 [ 0 => array:2 [ "nombre" => "Julia" "apellidos" => "Rey-Brandariz" ] 1 => array:2 [ "nombre" => "Alberto" "apellidos" => "Ruano-Ravina" ] 2 => array:2 [ "nombre" => "María Isolina" "apellidos" => "Santiago-Pérez" ] 3 => array:2 [ "nombre" => "Leonor" "apellidos" => "Varela-Lema" ] 4 => array:2 [ "nombre" => "Carla" "apellidos" => "Guerra-Tort" ] 5 => array:2 [ "nombre" => "Agustín" "apellidos" => "Montes" ] 6 => array:2 [ "nombre" => "María" "apellidos" => "Piñeiro" ] 7 => array:2 [ "nombre" => "Carlos" "apellidos" => "Rábade" ] 8 => array:2 [ "nombre" => "Mónica" "apellidos" => "Pérez-Ríos" ] ] ] ] ] "idiomaDefecto" => "es" "Traduccion" => array:1 [ "en" => array:9 [ "pii" => "S2387020624001451" "doi" => "10.1016/j.medcle.2023.11.020" "estado" => "S300" "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/S2387020624001451?idApp=UINPBA00004N" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0025775323007157?idApp=UINPBA00004N" "url" => "/00257753/0000016200000009/v1_202405080526/S0025775323007157/v1_202405080526/es/main.assets" ] "en" => array:21 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "Cardiovascular risk assessment in inflammatory bowel disease with metabolic dysfunction-associated steatotic liver disease" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "409" "paginaFinal" => "416" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Sandra García-Mateo, Samuel J. Martínez-Domínguez, Carla J. Gargallo-Puyuelo, Beatriz Gallego, Erika Alfambra, María C. Aso, Neus Martinez-Micaelo, Nuria Amigó, Javier Martínez-García, Pedro M. Baptista, Borja Sanz, Sara Ballesta, Judith Espinosa, Carlos Tejero, Fernando Gomollón" "autores" => array:15 [ 0 => array:4 [ "nombre" => "Sandra" "apellidos" => "García-Mateo" "email" => array:1 [ 0 => "sgarciamateo7@gmail.com" ] "referencia" => array:4 [ 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">1</span>" "identificador" => "fn0005" ] 3 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "Samuel J." 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"apellidos" => "Gargallo-Puyuelo" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 3 => array:3 [ "nombre" => "Beatriz" "apellidos" => "Gallego" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 4 => array:3 [ "nombre" => "Erika" "apellidos" => "Alfambra" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 5 => array:3 [ "nombre" => "María C." "apellidos" => "Aso" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 6 => array:3 [ "nombre" => "Neus" "apellidos" => "Martinez-Micaelo" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] 7 => array:3 [ "nombre" => "Nuria" "apellidos" => "Amigó" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "aff0020" ] ] ] 8 => array:3 [ "nombre" => "Javier" "apellidos" => "Martínez-García" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">e</span>" "identificador" => "aff0030" ] ] ] 9 => array:3 [ "nombre" => "Pedro M." "apellidos" => "Baptista" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">f</span>" "identificador" => "aff0035" ] ] ] 10 => array:3 [ "nombre" => "Borja" "apellidos" => "Sanz" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">g</span>" "identificador" => "aff0040" ] ] ] 11 => array:3 [ "nombre" => "Sara" "apellidos" => "Ballesta" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">h</span>" "identificador" => "aff0045" ] ] ] 12 => array:3 [ "nombre" => "Judith" "apellidos" => "Espinosa" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">h</span>" "identificador" => "aff0045" ] ] ] 13 => array:3 [ "nombre" => "Carlos" "apellidos" => "Tejero" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">h</span>" "identificador" => "aff0045" ] ] ] 14 => array:3 [ "nombre" => "Fernando" "apellidos" => "Gomollón" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] ] "afiliaciones" => array:8 [ 0 => array:3 [ "entidad" => "Department of Gastroenterology, “Lozano Blesa” University Clinical Hospital, 50009 Zaragoza, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Aragón Health Research Institute (IIS Aragón), 50009 Zaragoza, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "School of Medicine, University of Zaragoza, 50009 Zaragoza, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Biosfer Teslab, Plaça del Prim 10, 2on 5a, 43201 Reus, Spain" "etiqueta" => "d" "identificador" => "aff0020" ] 4 => array:3 [ "entidad" => "University of Zaragoza, Department of Multiscale in Mechanical and Biological Engineering, Spain" "etiqueta" => "e" "identificador" => "aff0030" ] 5 => array:3 [ "entidad" => "CIBER Enfermedades Hepáticas y Digestivas (CIBERehd), 28029 Madrid, Spain" "etiqueta" => "f" "identificador" => "aff0035" ] 6 => array:3 [ "entidad" => "Department of Endocrinology, Manises Hospital, 46940 Valencia, Spain" "etiqueta" => "g" "identificador" => "aff0040" ] 7 => array:3 [ "entidad" => "Department of Neurology, Lozano Blesa University Hospital, 50009 Zaragoza, Spain" "etiqueta" => "h" "identificador" => "aff0045" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Evaluación del riesgo cardiovascular en la enfermedad inflamatoria intestinal asociada a la enfermedad hepática grasa metabólica" ] ] "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" => 2287 "Ancho" => 2500 "Tamanyo" => 282685 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Flowchart of the study.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Inflammatory bowel diseases (IBDs) are chronic and inflammatory disorders that primarily affect the gastrointestinal tract but often have extraintestinal manifestations.<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">1</span></a> Among them, there has been increasing attention in recent years towards certain comorbidities, such as cardiovascular (CV) risk even in young patients,<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">2</span></a> and metabolic dysfunction-associated steatotic liver disease (MASLD).<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">3</span></a> Indeed, some authors suggest that IBD and MASLD may share certain pathophysiological pathways, including significant alterations in the composition of the intestinal microbiota.<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">4</span></a> CV diseases are the leading causes of morbidity and mortality in MASLD.<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">5</span></a> Since both IBD and MASLD have been independently associated with CV risk, it is conceivable that the combination of both conditions could further increase the risk of CV complications. However, systematic evaluation of CV risk in patients with IBD is still a subject of debate.</p><p id="par0010" class="elsevierStylePara elsevierViewall">While high total LDL cholesterol has been associated with CV events, these can occur even with normal LDL levels.<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">6</span></a> Furthermore, low LDL levels have been observed in patients with chronic inflammatory diseases such as rheumatoid arthritis, despite an increased CV risk.<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">7</span></a> In fact, despite the absence of data on this issue in IBD patients, total LDL cholesterol does not appear to be the appropriate biomarker for CV risk. In this way, a significant association has been found specifically with smaller and denser LDL particles and CV disease in other inflammatory diseases.<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">8</span></a> These particles are more likely to penetrate the endothelial barrier and are more prone to oxidation, thereby facilitating the progression of atherosclerotic plaques. However, this non-invasive approach may not reflect the cumulative exposure or CV risk factors, especially in young patients, who usually are in the moderate- or low-risk category of CV events according to guidelines. In that line, complementary assessment with ultrasound could be a useful, and non-invasive way to assess CV risk in those patients who are at moderate- to low-risk but have some risk factors such as IBD and MAFLD.<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">9</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Carotid artery intima-media thickness (CIMT) has been proposed as a reliable non-invasive imaging technique for assessing CV disease risk. CIMT measurements have already been used to demonstrate increased CV risk in IBD patients compared to matched healthy controls,<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">10</span></a> and some studies has showed a greater reduction in risk factors scores when the risk factor's advice is made in combination with both lipid profile and ultrasound imaging assessment. This effectiveness is reflected by including of vascular imaging in guidelines.<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">11</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">In this study, we specifically evaluate CV risk in a well-defined population of IBD patients with and without MASLD with both advanced lipoprotein profile and vascular imaging (CIMT) in a more comprehensive, non-invasive and effective manner of assessing CV risk.</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 design and study population</span><p id="par0025" class="elsevierStylePara elsevierViewall">This is a cross-sectional cohort study involving IBD adult outpatients conducted from October 2020 to April 2021 in a tertiary care Spanish hospital.</p><p id="par0030" class="elsevierStylePara elsevierViewall">A total of 941 consecutive IBD patients underwent clinical evaluations. Of them, 531 patients were excluded from the study due to various criteria. These exclusion criteria included being under 18 years of age, a non-stablished diagnosis of ulcerative colitis (UC) or Crohn's disease (CD), duration of IBD diagnosis less than 1 year, having viral hepatitis, engaging in high-risk alcohol intake (more than 20<span class="elsevierStyleHsp" style=""></span>g per day for women and more than 30<span class="elsevierStyleHsp" style=""></span>g per for men), prior history of CV disease, diagnosis of type 2 DM or impaired fasting glucose levels (100–125<span class="elsevierStyleHsp" style=""></span>mg/dL), and/or undergoing treatment for lipid disorders.</p><p id="par0035" class="elsevierStylePara elsevierViewall">Out of the remaining 410 patients with an established diagnosis of IBD and no other CV risk factors that could potentially confound the results, 310 patients could not be matched by sex, age, and the presence of MASLD, and a total sample of 50 patients with IBD and MASLD, as well as 50 patients with IBD without MASLD, were included in our analysis. These patients were matched for sex and age within a range of ±5 years). Please refer to <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a> for further details.</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Data collection and evaluated variables</span><p id="par0040" class="elsevierStylePara elsevierViewall">Data about IBD and its course and demographic information such as age, sex and presence of comorbidities (renal disease, smoking status, either hypercholesterolemia or hypertension (>120/80<span class="elsevierStyleHsp" style=""></span>mmHg) under any specific therapy), were evaluated.</p><p id="par0045" class="elsevierStylePara elsevierViewall">An anthropometric assessment was performed, including measurements of body mass index (BMI): underweight if <18<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">2</span>, normal if 18.5–25<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">2</span>, overweight<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>25–29.9<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">2</span> and obesity if BMI<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>30<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">2</span> and the waist–hip ratio (increased if >0.8 in women and >0.9 in men).</p><p id="par0050" class="elsevierStylePara elsevierViewall">Also, we assessed the patients’ lifestyle by administering the PREDIMED questionnaire to evaluate adherence to the Mediterranean diet. A score of ≥9 on the PREDIMED questionnaire is considered indicative of adequate adherence.<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">12</span></a> Furthermore, we utilized the Godin Leisure-time activity index to assess the level of physical exercise among the patients. Individuals with a score equal to or greater than 24 are classified as active.<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">13</span></a></p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Diagnostic criteria for IBD and MASLD. Definitions</span><p id="par0055" class="elsevierStylePara elsevierViewall">The diagnosis of IBD was based on clinical, endoscopic and histological parameters according to ECCO guidelines following Lennard–Jones criteria. IBD type (CD and UC), CD behaviour (inflammatory (B1), stricturing (B2) and penetrating (B3)),<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">14</span></a> CD location (ileal (L1), colonic (L2), ileocolonic (L3), upper tract involvement (L4), existence of perianal disease (p) and extension of UC (proctitis, left-side colitis, or extensive colitis) were categorized according to the Montreal classification.<a class="elsevierStyleCrossRefs" href="#bib0255"><span class="elsevierStyleSup">21,22</span></a> The disease was considered active if Harvey–Bradsraw index was higher than 4 points for CD and Mayo partial score over 2 points for UC patients.<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">14</span></a></p><p id="par0060" class="elsevierStylePara elsevierViewall">Diagnosis of MASLD was given in conformity with recent published criteria,<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">15</span></a> and patients with steatotic liver disease were included if they met any of the following criteria: BMI<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>25<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">2</span> or waist circumference<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>102/88<span class="elsevierStyleHsp" style=""></span>cm, blood pressure<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>130/85<span class="elsevierStyleHsp" style=""></span>mmHg or specific antihypertensive drug treatment, plasma triglycerides<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>150<span class="elsevierStyleHsp" style=""></span>mg/dL and plasma HDL-cholesterol<span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>40<span class="elsevierStyleHsp" style=""></span>mg/dL for males and ≤50<span class="elsevierStyleHsp" style=""></span>mg/dL for females.</p><p id="par0065" class="elsevierStylePara elsevierViewall">Steatotic liver disease was diagnosed based on both compatible ultrasonography images and controlled attenuation parameter (CAP™) greater than 248<span class="elsevierStyleHsp" style=""></span>dB/min.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Assessment of CV risk: carotid artery intima-media thickness (CIMT)</span><p id="par0070" class="elsevierStylePara elsevierViewall">CV risk assessed using carotid artery intima-media thickness (CIMT) as a reference to detect early atherosclerosis. CIMT measurements were obtained using B-mode ultrasound performed by two trained and qualified neurologist who were blinded to the clinical data and patient group classification, following the Mannheim criteria.<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">16</span></a> Measurements were taken at the distal third (10<span class="elsevierStyleHsp" style=""></span>mm) of the posterior wall of both the right and left common carotid arteries. Three measurements were taken, and the mean value was considered as the reference value. CIMT was classified as normal if it was below the 75th percentile for the patient's sex and age. We also assess the presence of plaque, which was defined as either CIMT<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>1.5<span class="elsevierStyleHsp" style=""></span>mm or the presence of focal thickening at least 50%.<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">17</span></a></p><p id="par0075" class="elsevierStylePara elsevierViewall">To study the impact of CV risk based on age, we categorized patients under 50 years old for men and under 40 years old for women as young patients. This age cutoff is based on guidelines that recommend starting CV screening.<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">18</span></a></p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Lipid profile through NMR spectroscopy</span><p id="par0080" class="elsevierStylePara elsevierViewall">A complete lipoprotein profile by NMR spectroscopy of each patient's blood sample was made. Serum samples were collected during the clinical evaluation. After the gathering, samples were centrifuged and stored aliquoted at −80<span class="elsevierStyleHsp" style=""></span>°C. The concentration of each lipoprotein particle subclass was calculated (Biosfer teslab, Reus, Spain) through signal of terminal methyl groups, and these same NMR signals are used to help calculate weighted-average lipoprotein particle sizes. Accordingly, the total amount of each particle, as well as triglycerides and cholesterol concentration and median particle's size were analyzed. Values from a Spanish population of reference were included as a comparison group for our IBD sample<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">19</span></a> considering as normal based on low/moderate CV risk: total cholesterol<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>200<span class="elsevierStyleHsp" style=""></span>mg/dL, LDL cholesterol<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>115<span class="elsevierStyleHsp" style=""></span>mg/dL, triglycerides<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>150<span class="elsevierStyleHsp" style=""></span>mg/dL, no-HDL cholesterol<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>145<span class="elsevierStyleHsp" style=""></span>mg/dL, VLDL particles<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>70<span class="elsevierStyleHsp" style=""></span>nmol/L, LDL particles<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>1150<span class="elsevierStyleHsp" style=""></span>nmol/L, small LDL particles<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>633<span class="elsevierStyleHsp" style=""></span>nmol/L, HDL particles<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>24<span class="elsevierStyleHsp" style=""></span>μmol/L, median HDL particles<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>8.2, VLDL size 52.03–42.36<span class="elsevierStyleHsp" style=""></span>nm, LDL size<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>20.91<span class="elsevierStyleHsp" style=""></span>nm, HDL size<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>8.21<span class="elsevierStyleHsp" style=""></span>nm. Content of cholesterol: VLDL-C<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>22<span class="elsevierStyleHsp" style=""></span>mg/dL, IDL-C<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>9<span class="elsevierStyleHsp" style=""></span>mg/dL, LDL-C<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>115<span class="elsevierStyleHsp" style=""></span>mg/dL, HDL-C<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>50 in women and >40 in men, no-HDL-C<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>145<span class="elsevierStyleHsp" style=""></span>mg/dL. Content of tryglicerides: VLDL-Tg<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>98<span class="elsevierStyleHsp" style=""></span>mg/dL, IDL-Tg<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>12<span class="elsevierStyleHsp" style=""></span>mg/dL, LDL-Tg<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>19<span class="elsevierStyleHsp" style=""></span>mg/Dl, HDL-Tg<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>12<span class="elsevierStyleHsp" style=""></span>mg/dL.</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Statistical analysis</span><p id="par0085" class="elsevierStylePara elsevierViewall">Statistical analysis was developed using SPSS software 26.0 for windows (IBM). Normality was assessed using Kolmogorov–Smirnov test. Qualitative variables were presented as numbers and percentages. Quantitative variables were showed as mean and standard deviation (SD) or interquartile range (IQR) in case of non-normal distribution. The relationship between categorical variables was assessed using Chi square test of Fisher's test, as appropriate. <span class="elsevierStyleItalic">T</span>-Student test or Mann–Whitney <span class="elsevierStyleItalic">U</span> test were used to compared means or quantitative variables. Finally, a logistic regression multivariable analysis was performed to evaluate the relationship between CIMT alterations, clinical characteristics, and advanced lipoprotein profile, and was presented by adjusted odds ratio (OR) and a 95% confidence interval (95% CI). All vascular risk factors with significance value in the univariate analysis and those with biologically relevance were included as confounding factors variables. For all test, a <span class="elsevierStyleItalic">p</span> value<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.005 was considered statistically significant.</p></span></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Results</span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Demographic, clinical and lifestyle characteristics of study population</span><p id="par0090" class="elsevierStylePara elsevierViewall">One hundred patients with IBD were included in the analysis, with 50 having MASLD and 50 without MASLD. Slightly over half of the patients were female (52%), and the mean age was 50 years.</p><p id="par0095" class="elsevierStylePara elsevierViewall">When comparing the MASLD patient group to the non-MASLD patient group, significant differences were observed in BMI (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001), the proportion of patients with a non-active lifestyle (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.032), C-reactive protein (CRP) values (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.004), and the need for systemic steroids within the past 5 years (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.039) (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0100" class="elsevierStylePara elsevierViewall">In terms of IBD, the average age at diagnosis was 36.44 years (SD 12.70). Fifty-one percent of patients had CD primarily located in the ileocolonic region (43%) and whereas regarding UC, 29% had an extensive form of the disease.</p><p id="par0105" class="elsevierStylePara elsevierViewall">Related to lifestyle factors, 69% of patients reported not following a Mediterranean diet, and only 23% of patients were classified as physically active (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">CIMT alteration and predictive factors</span><p id="par0110" class="elsevierStylePara elsevierViewall">Of the 100 patients evaluated, 58% had an abnormal CIMT. The mean value for right CIMT was 0.61 (IQR 0.53–0.69) and for the left one 0.62 (IQR 0.54–0.71). Of the whole cohort, 12% of the patients had a stablished plaque.</p><p id="par0115" class="elsevierStylePara elsevierViewall">According to univariate analysis presence of MASLD (36% vs 14%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.005), female sex (62% of women vs 38% of men, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.018) and inflammatory pattern in CD (B1) (22% vs 6%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.001) were risk factors of abnormal CIMT. No variables were statistically associated with a stablished plaque. After adjusting for all significant variables in the univariate analysis, in multivariate analysis, only MASLD (OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>5.05, CI 95%<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.71–14.92, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.003) and female sex (OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>3.32, CI 95%<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.03–10, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.033) were significantly associated with CIMT alterations. No statistical differences were observed regarding smoking patterns, renal disease, hypertension, BMI, waist-hip ratio, IBD type, location, or behaviour. Similarly, no associations were found between the presence of extra-intestinal manifestations, need for surgery, IBD therapy, steroid dependence, number of cycles of systemic steroids, or lifestyle factors and CIMT abnormalities.</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">CIMT alteration and predictive factors in young patients</span><p id="par0120" class="elsevierStylePara elsevierViewall">Out of the 100 patients with IBD evaluated, 32% were under the age of 40 (for men) or 50 (for women). More than half of these young patients (56.2%) had an altered CIMT (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.808), being higher in women (12 out of 19, 63.2%) compared to men (6 out of 13, 46.2%), as detailed in <a class="elsevierStyleCrossRef" href="#sec0100">supplementary material 1</a>.</p><p id="par0125" class="elsevierStylePara elsevierViewall">No factors assessed were associated with an increased risk of altered CIMT in this subpopulation, but young patients with MASLD showed a clear tendency to have a higher frequency of CIMT alterations (61 vs 28.6%) (<a class="elsevierStyleCrossRef" href="#sec0100">supplementary material 2</a>).</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Lipoprotein profile studied by NMR spectroscopy and CIMT alterations</span><p id="par0130" class="elsevierStylePara elsevierViewall">In the univariate analysis (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> and <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>), it is worth noting that patients with altered total cholesterol (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.031), non-HDL cholesterol (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.021), dense LDL with high cholesterol (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.021) and triglyceride density (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.025) showed a significant association with CIMT alterations. However, no such association was found between total LDL cholesterol and carotid study alterations (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.108).</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0135" class="elsevierStylePara elsevierViewall">In the multivariate analysis, considering all the aforementioned significant variables, the association between LDL particles with high cholesterol density and CIMT alterations was confirmed for the overall patient cohort (OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>3.62, 95% CI<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.07–12.19, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.038). However, within the subgroup of patients aged below 40–50 years old, the relationship was observed with LDL particles exhibiting high triglyceride concentration (OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>5.98, 95% CI<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.03–34.48, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.046).</p></span></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Discussion</span><p id="par0140" class="elsevierStylePara elsevierViewall">Atherosclerosis is widely acknowledged as a leading cause of mortality and disability globally, and the detection of subclinical atherosclerosis has proven to be an invaluable tool for predicting CV events.<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">20</span></a></p><p id="par0145" class="elsevierStylePara elsevierViewall">Recent evidence suggests that patients with IBD exhibit accelerated atherosclerosis and an increased risk of CV morbidity compared to the general population.<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">21</span></a> Indeed, in a recent published meta-analysis of 2330 IBD patients and 2032 matched controls, it was found significant increased of CIMT in IBD patients when compared with controls.<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">22</span></a> In our study, we found that 58% of patients had abnormal CIMT, and 12% had stablished plaques. These findings are consistent with other IBD cohorts reporting CIMT measurements, with prevalence of CIMT alterations around 42% of IBD patients.<a class="elsevierStyleCrossRefs" href="#bib0200"><span class="elsevierStyleSup">10,23</span></a></p><p id="par0150" class="elsevierStylePara elsevierViewall">One of the most extensively validated hypotheses to explain the heightened CV risk in patients with IBD is the presence of chronic systemic inflammation.<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">2</span></a> However, this increased CV risk remains evident even when IBD is well-managed,<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">24</span></a> and according to our study, this fact is also independent of having required cycles of systemic corticosteroids, having a corticosteroid-dependent course, needing surgery, or second-line biologics for the control of inflammatory activity. To delve deeper into this issue, it is essential to consider the association with other underdiagnosed CV factors, such as MASLD.</p><p id="par0155" class="elsevierStylePara elsevierViewall">In this regard, patients with MASLD exhibited a five-fold risk of subclinical atherosclerosis, based on CIMT alterations (OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>5.05, CI 95%<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.71–14.92, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.003) compared to those without MASLD. This finding could be explained by the fact that while patients with steatotic liver disease have demonstrated an elevated incidence of CV events,<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">5</span></a> those with MASLD face an even greater risk when compared to both steatotic liver disease<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">25</span></a> and healthy controls, regardless of sex.</p><p id="par0160" class="elsevierStylePara elsevierViewall">The other risk factor for subclinical atherosclerosis found in our study is female sex (OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>3.322, 95% CI<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.03–10). This finding is consistent with previous reports indicating that women with IBD have a higher risk of CV pathology, including an increased incidence of coronary artery disease and stroke.<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">21</span></a> This difference may be explained by higher levels of inflammation related to reproductive hormone levels and their increased frequency of inflammatory-mediated autoimmune diseases, which contribute to higher mean C-reactive protein (CRP) values in females compared to males.<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">26</span></a> However, this association was not replicated in a large French cohort, where age and severe disease, rather than sex, were identified as the main risk factors for CV disease in patients with IBD.<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">2</span></a> Therefore, further studies may be necessary to elucidate the relationship between sex and CV risk in patients with IBD.</p><p id="par0165" class="elsevierStylePara elsevierViewall">Although BMI and physical activity did not show a direct relationship with CIMT alterations, their link to CV risk in these patients can be understood indirectly though the presence of MASLD. According to our results and in concordance with published literature,<a class="elsevierStyleCrossRef" href="#bib0285"><span class="elsevierStyleSup">27</span></a> patients with IBD and MASLD have significantly higher BMI and a less active lifestyle than patients without MASLD. These two characteristics are dramatically associated with the development of CV risk through pathophysiology pathways that links them to the development of MASLD. For instance, increased intrahepatic lipogenesis and decreased gut microbiota diversity with heightened intestinal permeability and release of proinflammatory citokines and lipopolisacharides which contribute to an increased risk of atherosclerosis.<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">28</span></a></p><p id="par0170" class="elsevierStylePara elsevierViewall">In terms of dietary patterns, the Mediterranean diet has previously been associated with a reduced risk of CV disease, as demonstrated in the PREDIMED study.<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">12</span></a> This could be explained by the fact that the Mediterranean diet is rich in fibre, vegetables, fish and fruit, and low in processed and red meats. The consumption of low fibre and red and processed meat, enriched in L-carnitine, is closely linked to the production of TMAO (trimethylamine N-oxide), which when released into the bloodstream is associated with the production of atherosclerosis.<a class="elsevierStyleCrossRef" href="#bib0295"><span class="elsevierStyleSup">29</span></a> However, it did not emerge as a protective factor for CV health based on CIMT measurements in our study. It is important to note that patients with IBD typically undergo regular check-ups and monitoring by their physicians, which may result in a patient population that is more inclined towards thorough self-care practices, including adherence to a healthier diet, compared to individuals without IBD.</p><p id="par0175" class="elsevierStylePara elsevierViewall">CV risk has traditionally been assessed using indirect and non-invasive scores, such as the SCORE2 algorithm,<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">18</span></a> which was designed and validated for otherwise healthy individuals aged over 50 (women) or over 40 (men), as it has been demonstrated that other age ranges have a lower CV risk despite the presence of CV risk factors or conditions such as MASLD or IBD.<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">5</span></a> However, is crucial not to trivialize the CV risk in young patients with IBD.<a class="elsevierStyleCrossRefs" href="#bib0160"><span class="elsevierStyleSup">2,21</span></a> In fact, in our study, 56.2% of patients under the age of 40 and 50, stratified by sex, exhibited CIMT alterations. Consistent with our findings, a recent study showed that up to 35% of IBD patients with low CV risk based on SCORE charts were reclassified to high CV risk after evaluation by CIMT ultrasound.<a class="elsevierStyleCrossRef" href="#bib0300"><span class="elsevierStyleSup">30</span></a></p><p id="par0180" class="elsevierStylePara elsevierViewall">A detailed description of the association between CV disease and IBD with an advanced lipoprotein profile has yet to be provided. Based on our results, we observed that dense LDL particles are associated with CIMT alterations, particularly those with higher levels of cholesterol concentration (for the whole cohort: OR 3.623, 95% CI (1.07–12.19), <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.038), and those richer in triglycerides for younger patients (OR 5.98, 95% CI (1.03–34.48), <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.046). Interestingly, the total number of LDL particles was not significantly higher in patients with elevated CV risk. This is consistent with the results published by Hernández-Camba, in which LDL cholesterol levels were not different between controls and IBD cases despite the latter having a higher rate of CIMT alterations.<a class="elsevierStyleCrossRef" href="#bib0300"><span class="elsevierStyleSup">30</span></a> These findings align with the growing interest among scientific communities in exploring the involvement of dense LDL in the pathogenesis of CV risk.<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">8</span></a> In other words, the focus is shifting towards the characteristics of the particles themselves rather than the total quantity of LDL. Therefore, our results suggest that NMR spectroscopy could play an essential role in detecting and classifying dense LDL particles in patients with IBD. Despite the usefulness of this promising method, when available, it is advisable to conduct a combined evaluation, both of lipoproteins before and after initiating targeted treatment, as well as through imaging test. This is because, as we have demonstrated, in some instances, the analytical values do not correlate with the actual CV risk.</p><p id="par0185" class="elsevierStylePara elsevierViewall">Our study has several limitations. Firstly, we did not use NMR imaging, which is considered the cold standard for diagnosing fatty liver disease, nor did we perform liver biopsies. However, previous research has shown that the combination of controlled attenuation parameter (CAP) and ultrasonography is clinically valuable. The small sample size was influenced by strict inclusion criteria and limited budget for NMR spectroscopy, which was used for detailed lipoprotein analysis. Additionally, our study relied on cross-sectional data without longitudinal follow-up, which should be taken into consideration. Nevertheless, this is a very specific population that has been extensively studied from the perspective of CV comorbidity. For the first time, the study has combined the assessment of lipoprotein profile with the presence or absence of MASLD and CIMT abnormalities to achieve a better understanding of the CV risk in patients with IBD.</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Conclusions</span><p id="par0190" class="elsevierStylePara elsevierViewall">In conclusion, screening for MASLD should be a standard part of the clinical evaluation for IBD patients as a crucial and underdiagnosed risk factor for CV disease. CIMT measurement and detailed lipid profile analysis should be considered, if possible, together for all IBD patients regardless of age, to achieve a better guide of lipid lowering therapy. Further studies focusing on sex-specific analyses, lipid profiles, and longitudinal evaluations are clearly needed to enhance our understanding of these associations.</p></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Ethical considerations</span><p id="par0195" class="elsevierStylePara elsevierViewall">This study was conducted in agreement with the Helsinki Declaration and authorized by the Ethics and Clinical Research Committee of Aragon (Spain) with the approval code: C.I. PI20/548.</p></span><span id="sec0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Financial support</span><p id="par0200" class="elsevierStylePara elsevierViewall">This work has been carried out thanks of clinical grant provided by <span class="elsevierStyleGrantSponsor" id="gs1">GETECCU (Grupo Español de Trabajo en Enfermedad de Crohn y Colitis Ulcerosa)</span> and <span class="elsevierStyleGrantSponsor" id="gs2">DGA (Diputación General de Aragón)</span>.</p></span><span id="sec0090" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0150">Conflict of interest</span><p id="par0205" class="elsevierStylePara elsevierViewall">N. Amigó is a stock owner of Biosfer Teslab, and has a patent for an NMR method for lipoprotein characterization. Professor Gomollón has received payments for lectures from Abbvie, Janssen, Takeda, MSD, and Pfizer. His research group has received unrestricted grants for research from Janssen, Abbvie, and GETECCU.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:13 [ 0 => array:3 [ "identificador" => "xres2141269" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background and aims" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1817793" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres2141270" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Antecedentes y objetivos" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1817792" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Materials and methods" "secciones" => array:6 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Study design and study population" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Data collection and evaluated variables" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Diagnostic criteria for IBD and MASLD. Definitions" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Assessment of CV risk: carotid artery intima-media thickness (CIMT)" ] 4 => array:2 [ "identificador" => "sec0035" "titulo" => "Lipid profile through NMR spectroscopy" ] 5 => array:2 [ "identificador" => "sec0040" "titulo" => "Statistical analysis" ] ] ] 6 => array:3 [ "identificador" => "sec0045" "titulo" => "Results" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0050" "titulo" => "Demographic, clinical and lifestyle characteristics of study population" ] 1 => array:2 [ "identificador" => "sec0055" "titulo" => "CIMT alteration and predictive factors" ] 2 => array:2 [ "identificador" => "sec0060" "titulo" => "CIMT alteration and predictive factors in young patients" ] 3 => array:2 [ "identificador" => "sec0065" "titulo" => "Lipoprotein profile studied by NMR spectroscopy and CIMT alterations" ] ] ] 7 => array:2 [ "identificador" => "sec0070" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0075" "titulo" => "Conclusions" ] 9 => array:2 [ "identificador" => "sec0080" "titulo" => "Ethical considerations" ] 10 => array:2 [ "identificador" => "sec0085" "titulo" => "Financial support" ] 11 => array:2 [ "identificador" => "sec0090" "titulo" => "Conflict of interest" ] 12 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2023-09-05" "fechaAceptado" => "2023-11-28" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1817793" "palabras" => array:5 [ 0 => "Inflammatory bowel disease" 1 => "Metabolic disfunction-associated steatotic liver disease" 2 => "Cardiovascular risk" 3 => "Carotid artery intima-media thickness" 4 => "Dense LDL" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1817792" "palabras" => array:5 [ 0 => "Enfermedad inflamatoria intestinal" 1 => "Enfermedad hepática esteatósica asociada a disfunción metabólica" 2 => "Riesgo cardiovascular" 3 => "Grosor íntima-media carotídeo" 4 => "Partículas de baja densidad" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background and aims</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Inflammatory bowel disease (IBD) has been reported to increase the risk of early atherosclerosis even in young patients. Moreover, metabolic dysfunction-associated steatotic liver disease (MASLD), which has been linked to IBD, is a well-recognized but underdiagnosis entity related to cardiovascular risk. We analyze the impact of MASLD in IBD patients’ cardiovascular risk through both advanced lipoprotein profile sorted by nuclear magnetic resonance spectroscopy, and carotid artery intima-media thickness (CIMT).</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Cross-sectional cohort study which involves 941 IBD adult outpatients. Of them, 50 patients with IBD who met criteria for MASLD and 50 with IBD without MASLD, matched by sex and age were included. Alterations in CIMT were evaluated considering abnormal measures above the 75th percentile adjusted for sex and age. Specific advanced lipoprotein profile was also carried out.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Most of the patients had an abnormal CIMT (58%). MASLD (OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>5.05, CI 95%<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.71–14.92) and female sex (OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>3.32, CI 95%<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.03–10) were significantly associated with CIMT alterations. Dense LDL particles (with high cholesterol composition in general cohort (OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>3.62, 95% CI<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.07–12.19) and high triglycerides density in young subgroup (OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>6.25, 95% CI<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.04–50) but not total LDL cholesterol were associated with CIMT alterations.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">MASLD and female sex are associated with early atherosclerosis in IBD patients. Dense LDL particle in combination with vascular imaging findings should be evaluated as non-invasive tools in the management of cardiovascular risk in IBD patients.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background and aims" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Antecedentes y objetivos</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Se ha descrito que la enfermedad inflamatoria intestinal (EII) incrementa el riesgo de aterosclerosis precoz incluso en pacientes jóvenes. Además, la esteatosis hepática metabólica (MASLD), entidad relacionada con la EII, es una causa reconocida pero infradiagnosticada de riesgo cardiovascular. Hemos analizado el impacto de MASLD en el desarrollo de enfermedades cardiovasculares en los pacientes con EII a través de un estudio avanzado del perfil de lipoproteínas con espectroscopia por resonancia magnética nuclear y el grosor íntima-media carotídeo (GIMc).</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Métodos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Se trata de un estudio de cohortes transversal de 941 pacientes ambulatorios con EII. De ellos, se incluyeron 50 con EII que cumplían criterios de MASLD y otros 50 con EII sin MASLD emparejados por sexo y edad. Se evaluaron las alteraciones de GIMc considerando patológicos aquellos valores por encima del percentil 75 ajustado por sexo y edad. Se analizó también el perfil avanzado de lipoproteínas.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Muchos de los pacientes tuvieron un GIMc alterado (58%). La presencia de MASLD (<span class="elsevierStyleItalic">odds ratio</span> [OR]<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>5,05, intervalo de confianza [IC] 95%<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1,71-14,92) y el sexo femenino (OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>3,32, IC 95%<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1,03-10), se asociaron significativamente a las alteraciones de GIMc. Las partículas de baja densidad (LDL) (con alta concentración de colesterol en la cohorte general [OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>3,62, IC 95%<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1,07-12,19], así como de de triglicéridos en el subgrupo de pacientes jóvenes [OR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>6,25, IC 95%<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1,04-50]), pero no las cifras de colesterol LDL total, se asociaron a alteraciones en el GIMc.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">La presencia de MASLD y el sexo femenino se asocian a aterosclerosis precoz en los pacientes con EII. El estudio de las partículas LDL densas en combinación con los hallazgos en las pruebas de imagen vascular, deberían valorarse como herramientas no invasivas de detección de riesgo cardiovascular en los sujetos con EII.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Antecedentes y objetivos" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] ] "NotaPie" => array:1 [ 0 => array:3 [ "etiqueta" => "1" "nota" => "<p class="elsevierStyleNotepara" id="npar0020">Dual first authorship due to equal contribution.</p>" "identificador" => "fn0005" ] ] "apendice" => array:1 [ 0 => array:1 [ "seccion" => array:1 [ 0 => array:4 [ "apendice" => "<p id="par0215" class="elsevierStylePara elsevierViewall">The following are the supplementary data to this article:<elsevierMultimedia ident="upi0005"></elsevierMultimedia></p>" "etiqueta" => "Appendix A" "titulo" => "Supplementary data" "identificador" => "sec0100" ] ] ] ] "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" => 2287 "Ancho" => 2500 "Tamanyo" => 282685 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Flowchart of the study.</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" => 1457 "Ancho" => 1508 "Tamanyo" => 124667 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Star diagram of carotid silhouette simulator based on advanced lipoprotein profile in patients with IBD based on CIMT alterations. The black circumference represents the normal values of the general population, the orange represents the values of patients with IBD and normal CIMT, and the red one represents the values of patients with IBD and altered CIMT. LDL: low density lipoprotein, HDL: high density lipoprotein, VLDL: very low density lipoprotein, tot: total, C: cholesterol, Tg: triglycerides.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">WHR: waist–hip ratio.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">Patients’ 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">Total cohort \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Without MASLD \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">With MASLD \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"><span class="elsevierStyleItalic">p</span>-Value<a class="elsevierStyleCrossRef" href="#tblfn0010">**</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \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">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>50 \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">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>50 \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" 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"><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">Women, 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">52 (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">24 (51.1) \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">22 (53.7) \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">0.808 \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">Age, m (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">50 (12.1) \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">50 (11.6) \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">50 (12.8) \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">0.870 \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">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">11 (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">8 (16) \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 (6) \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">0.110 \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">Former-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">51 (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">24 (48) \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 (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">0.548 \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">17 (17) \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">5 (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">12 (24) \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">0.062 \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="5" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Body mass index, n (%)</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="elsevierStyleHsp" style=""></span>Low weigh \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 (2) \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 (4) \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 (0) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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>Normal weigh \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">34 (34) \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">31 (62) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></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>Overweigh \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">40 (40) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 (32) \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">24 (48) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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>Obesity \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">24 (24) \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) \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 (46) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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="5" 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">High WHR, 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">51 (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">23 (46) \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 (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">0.317 \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">Age at diagnosis, m (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">36 (26.3–45) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">36 (25–45) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">32 (26.5–40) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.621 \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="5" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Disease location, n (%)</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="elsevierStyleHsp" style=""></span>Crohn disease (CD) \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">51 (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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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>Colonic CD \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 (15.6) \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">5 (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">3 (6) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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>Ileocolonic CD \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">43 (843) \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 (36) \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">25 (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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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>Ulcerative colitis (UC) \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 (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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">0.156 \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>Left side colitis \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">20 (40.8) \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 (16) \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 (24) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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>Extensive colitis \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">29 (59.1) \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">19 (38) \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 (20) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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="5" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Disease behaviour (CD), n (%)</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="elsevierStyleHsp" style=""></span>Stricturing \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 (31.3) \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 (14) \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 (18) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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>Inflammatory \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 (54.9) \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 (24) \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 (32) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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>Penetrating \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 (13.7) \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 (8) \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 (6) \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">0.688 \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="5" 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">Extraintestinal 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">24 (24) \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">14 (28) \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 (20) \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">0.349 \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">Need of surgery, 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">19 (19) \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 (19.1) \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">10 (24.4) \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">0.551 \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">Two or more surgeries, 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 (9) \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">5 (10.6) \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 (8) \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">0.892 \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="5" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Therapy, n (%)</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="elsevierStyleHsp" style=""></span>5-ASA \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">35 (35) \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 (34) \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 (36) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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>Anti-TNF \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 (23) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11 (22) \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 (24) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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>Other biologics<a class="elsevierStyleCrossRef" href="#tblfn0005">*</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15 (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">7 (14) \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 (16) \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">0.935 \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>Azathioprine \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 (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">6 (12) \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 (8) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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>Azathioprine<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>anti-TNF \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 (6) \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 (8) \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 (4) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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>Without treatment \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">11 (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">5 (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">6 (12) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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="5" 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">Steroid-dependent course, 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">32 (32) \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 (36) \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">14 (28) \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">0.391 \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">Need of systemic steroids in last 5 years, 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">38 (38) \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">14 (28) \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">24 (48) \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">0.039 \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">Active 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">6 (6) \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 (8) \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 (4) \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">0.400 \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">Calprotectin, m (IRQ)</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">88.4 (24–376.7) \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">86.5 (24–446.7) \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">125.2 (39.7–326.4) \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">0.632 \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">CRP (mg/L), m (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">2.9 (1.6–5.8) \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">2.1 (1.0–4.9) \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">4.3 (2.1–7.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.004 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-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">Adherence to MD, 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">31 (31) \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">20 (40) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11 (22) \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">0.052 \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">Active lifestyle, 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 (23) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 (32) \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 (14) \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">0.032 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3529823.png" ] ] ] "notaPie" => array:2 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "*" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Ustekinumab, vedolizumab or tofacitinib. MD: Mediterranean diet, CRP: C-reactive protein, <span class="elsevierStyleItalic">n</span>: total number, <span class="elsevierStyleItalic">m</span>: mean, IQR: interquartile range, SD: standard deviation, IBD: inflammatory bowel disease, CD: Crohn's disease, UC: ulcerative colitis, 5-ASA: 5 aminosalicylates.</p>" ] 1 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "**" "nota" => "<p class="elsevierStyleNotepara" id="npar0010">Univariate analysis comparing IBD and MASLD and IBD without MASLD.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Demographic, anthropometric, lifestyle and characteristics of IBD patients and its association with MASLD.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">NMR: nuclear magnetic resonance, LDL: low density lipoproteins, HDL: high density lipoproteins, ld: low and dense, C: cholesterol, Tg: triglycerides, VLDL: very low and dense lipoprotein.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"> \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 " colspan="3" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Total study population</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="3" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Young subpopulation</th></tr><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">Advanced lipoprotein profile assessed by NMR spectroscopy \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">Normal CIMT <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>42 \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">CIMT alteration <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>58 \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="#tblfn0015">*</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">Normal CIMT <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>14 \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">CIMT alteration <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>18 \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="#tblfn0015">*</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">Total colesterol. High, <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">25 (59.5) \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">46 (79.3) \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">0.031 \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 (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">13 (72.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.198 \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. High, <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">9 (21.4) \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 (20.7) \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">0.929 \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 (28.6) \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 (16.7) \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">0.419 \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">Total LDL. High, <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">29 (69) \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">48 (82.8) \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">0.108 \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 (64.3) \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">13 (72.2) \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">0.631 \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">Total HDL. Low, <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">10 (23.8) \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 (17.2) \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">0.418 \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 (14.3) \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 (11.1) \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">0.788 \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">VLDL total. High, <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">9 (21.4) \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 (20.7) \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">0.929 \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 (28.6) \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 (16.7) \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">0.419 \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">Ld LDL. High, <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">27 (64.3) \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">39 (67.2) \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">0.758 \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 (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">9 (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">0.688 \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">No-HDL. High, <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 (28.6) \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">30 (51.7) \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">0.021 \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 (21.4) \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 (44.4) \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">0.174 \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">VLDL-C. High, <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">8 (19) \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 (17.2) \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">0.817 \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 (28.6) \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 (11.1) \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">0.209 \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">IDL-C. High, <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">23 (54.8) \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 (70.7) \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">0.101 \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 (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">12 (66.7) \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">0.581 \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">LDL-C. High, <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">27 (64.3) \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">52 (89.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.002 \t\t\t\t\t\t\n \t\t\t\t</td><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 (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">15 (83.3) \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">0.102 \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">HDL-C. High, <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 (14.3) \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 (15.5) \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">0.865 \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 (21.4) \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 (5.6) \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">0.295 \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">VLDL-TG. High, <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">9 (21.4) \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 (20.7) \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">0.929 \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">5 (35.7) \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 (16.7) \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">0.217 \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">LDL-TG. High, <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">11 (26.2) \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 (48.3) \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">0.025 \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 (14.3) \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 (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">0.065 \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">HDL-TG. High, <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">27 (64.3) \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 (70.7) \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">0.498 \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 (85.7) \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">14 (77.8) \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">0.672 \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">VLDL size, Altered, <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">16 (38.1) \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">27 (46.6) \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">0.399 \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">5 (35.7) \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 (55.6) \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">0.265 \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">LDL size. Altered, <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">9 (21.4) \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 (15.5) \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">0.448 \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 (21.4) \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 (5.6) \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">0.295 \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">HDL size. Altered, <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">5 (11.9) \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 (13.8) \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">0.782 \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 (14.3) \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 (5.6) \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">0.568 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3529824.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0015" "etiqueta" => "*" "nota" => "<p class="elsevierStyleNotepara" id="npar0015">Univariate analysis.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Lipoprotein profile by NMR spectroscopy and its relationship with CIMT alterations.</p>" ] ] 4 => array:5 [ "identificador" => "upi0005" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => false "mostrarDisplay" => true "Ecomponente" => array:2 [ "fichero" => "mmc1.doc" "ficheroTamanyo" => 19786 ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:30 [ 0 => array:3 [ "identificador" => "bib0155" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Comorbidities in inflammatory bowel disease: a call for action" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "M. 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Original article
Cardiovascular risk assessment in inflammatory bowel disease with metabolic dysfunction-associated steatotic liver disease
Evaluación del riesgo cardiovascular en la enfermedad inflamatoria intestinal asociada a la enfermedad hepática grasa metabólica
Sandra García-Mateoa,b,1,
, Samuel J. Martínez-Domíngueza,b,1, Carla J. Gargallo-Puyueloa,b, Beatriz Gallegob, Erika Alfambrab, María C. Asoa,b, Neus Martinez-Micaeloc, Nuria Amigóc,d, Javier Martínez-Garcíab,e, Pedro M. Baptistab,f, Borja Sanzg, Sara Ballestah, Judith Espinosah, Carlos Tejeroh, Fernando Gomollóna,c
Autor para correspondencia
a Department of Gastroenterology, “Lozano Blesa” University Clinical Hospital, 50009 Zaragoza, Spain
b Aragón Health Research Institute (IIS Aragón), 50009 Zaragoza, Spain
c School of Medicine, University of Zaragoza, 50009 Zaragoza, Spain
d Biosfer Teslab, Plaça del Prim 10, 2on 5a, 43201 Reus, Spain
e University of Zaragoza, Department of Multiscale in Mechanical and Biological Engineering, Spain
f CIBER Enfermedades Hepáticas y Digestivas (CIBERehd), 28029 Madrid, Spain
g Department of Endocrinology, Manises Hospital, 46940 Valencia, Spain
h Department of Neurology, Lozano Blesa University Hospital, 50009 Zaragoza, Spain