Can the COPD-comorbidome Be Applied to All Outpatients With Chronic Obstructive Pulmonary Disease? A Single-center Analysis

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A Single-center Analysis" "tieneTextoCompleto" => true "saludo" => "Dear Editor:" "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "591" "paginaFinal" => "593" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Juan Marco Figueira Gonçalves, Miguel Ángel García Bello, María Dolores Martín Martínez, Ignacio García-Talavera, Rafael Golpe" "autores" => array:5 [ 0 => array:4 [ "nombre" => "Juan Marco" "apellidos" => "Figueira Gonçalves" "email" => array:1 [ 0 => "juanmarcofigueira@gmail.com" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "Miguel Ángel" "apellidos" => "García Bello" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] ] ] 2 => array:3 [ "nombre" => "María Dolores" "apellidos" => "Martín Martínez" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "c" "identificador" => "aff0015" ] ] ] 3 => array:3 [ "nombre" => "Ignacio" "apellidos" => "García-Talavera" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 4 => array:3 [ "nombre" => "Rafael" "apellidos" => "Golpe" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "d" "identificador" => "aff0020" ] ] ] ] "afiliaciones" => array:4 [ 0 => array:3 [ "entidad" => "Pneumology and Thoracic Surgery Service, University Hospital Nuestra Señora de la Candelaria (HUNSC), Santa Cruz de Tenerife, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Division of Clinical Epidemiology and Biostatistics, Research Unit, University Hospital Nuestra Señora de la Candelaria (HUNSC), and Primary Care Management, Santa Cruz de Tenerife, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Clinical Analysis Service, University Hospital Nuestra Señora de la Candelaria (HUNSC), Santa Cruz de Tenerife, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Respiratory Medicine Service, University Hospital Lucus Augusti, Lugo, Spain" "etiqueta" => "d" "identificador" => "aff0020" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "¿El comorbidoma de COPD se puede aplicar a todos los pacientes ambulatorios con enfermedad pulmonar obstructiva crónica? Un estudio unicéntrico" ] ] "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" => 1691 "Ancho" => 2083 "Tamanyo" => 145087 ] ] "descripcion" => array:1 [ "en" => "The “comorbidome” is a graphic expression of comorbities with more than 5% prevalence in the entire cohort. The area of the circles relates to the prevalence of the disease. The proximity to the center (mortality) express the strength of the association between the disease and the risk of death. This was scaled from the inverse of the HR (1/HR). The dotted line represents HR=1. Beyond the line, HR are less than 1. The red bubble represents statistical significance association (HR>1; P<.05). Abbreviations: HF: heart failure. CKD: chronic kidney disease. IHD: ischemic heart disease. CVA: cerebrovascular accidents. DM: diabetes mellitus. DLP: dyslipidemia. PADs: peripheral arterial disease." ] ] ] "textoCompleto" => "Cardiovascular diseases, lung cancer, diabetes mellitus, osteoporosis, anxiety, and depression are among the most prevalent comorbidities in patients with chronic obstructive pulmonary disease (COPD)<a class="elsevierStyleCrossRefs" href="#bib0055">1,2</a> and have a negative impact in both their quality of life as well as their survival.<a class="elsevierStyleCrossRefs" href="#bib0065">3,4</a> Divo et al.<a class="elsevierStyleCrossRef" href="#bib0070">4</a> developed the COTE (COPD Specific Comorbidity Test) index after evaluating 1664 patients with COPD. Cancers of the lung, esophagus, breast, and pancreas, liver cirrhosis, atrial fibrillation or flutter, coronary heart disease, diabetes-associated neuropathy, pulmonary fibrosis, congestive heart failure, gastroduodenal ulcer, and anxiety were the pathologies with the greatest impact on the vital prognosis. Based on these findings, the group designed a bubble chart (mimicking the solar system) of the prevalence of these pathologies and their association with mortality and named it a “comorbidome”. However, distributions within this chart seem to be alterable and depend on the study population (in hospital vs outpatients).<a class="elsevierStyleCrossRefs" href="#bib0070">4,5</a> Therefore, we wondered whether the distribution of the comorbidome described by Divo et al. could vary even among different outpatient populations with COPD.Our group has recently outlined that comorbidities, particularly the cardiovascular and psychiatric ones, impact the quality of life of patients with COPD (measured through the COMCOLD index), especially in the more symptomatic sub-groups according to the GOLD (Global Initiative for Chronic Obstructive Lung Disease) 2017 classification.<a class="elsevierStyleCrossRef" href="#bib0080">6</a> In the present work, we performed a sub-analysis of the same population, aimed at reproducing the comorbidome depicted by Divo et al.,<a class="elsevierStyleCrossRef" href="#bib0070">4</a> and evaluated (1) the impact of a panel of comorbidities on the survival of our outpatients with COPD and (2) their distribution within that comorbidome chart.Briefly, retrospective observational study was performed on follow-up outpatients with COPD. Inclusion criteria were: age ≥40 years, current or former smoker with a pack-year index (PYI) ≥10 and a forced expiratory volume in the first second (FEV1)/forced vital capacity (FVC) ratio <0.70 past salbutamol administration. Exclusion criteria were chronic airflow obstruction and a PYI<10 or any pathology different from COPD. Patients were stratified according to the GOLD 2017 document. Information on the following comorbidities, included in the Charlson comorbidity index, was collected: myocardial infarction, angina, cardiovascular disease, cerebrovascular disease, dementia, COPD, connective tissue disease, gastrointestinal disease, mild or severe liver disease, complicated or uncomplicated diabetes mellitus, stroke, kidney failure, cancer, leukemia, lymphoma, secondary metastasis, and AIDS. Additionally evaluated pathologies were: arterial hypertension, dyslipidemia, cardiac arrhythmia, peripheral arterial disease, asthma, anxiety, and depression.Qualitative variables were expressed as absolute values and percentages, while quantitative variables were summarized as means±SD. Cox logistic regression and Kaplan–Meier statistics were applied for time-dependent variables. The study was approved by the Clinical Research Ethics Committee of the University Hospital Nuestra Señora de la Candelaria (Spain). The comorbidome was plotted according to the original design of Divo et al.,<a class="elsevierStyleCrossRef" href="#bib0070">4</a> where the circle diameter expressed the prevalence of the distinct comorbidities in percent and the distance of the circles to the center the risk of death based on the numerical value of the hazard ratio. The comorbidome represents comorbidities with a prevalence of more than 5% in the entire cohort.A total of 439 patients were included in the study. The cohort characteristics had been described in a previous work.<a class="elsevierStyleCrossRef" href="#bib0080">6</a> The patients’ mean age was 70; most of them were males with a predicted FEV1% of 55±20; 35% of them were current smokers. According to the GOLD 2017 categories, 142 (32%) were classified as GOLD A, 207 (48%) as GOLD B, 10 (2%) as GOLD C, and 80 (18%) as GOLD D. The mean Charlson index was 2.5±1.5.During the follow-up period of 53 months, 131 patients (30%) died. Surviving patients were followed up for at least 41 months and a maximum of 88.5 months. The prevalence of comorbidities in both survivors and deceased patients is shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>. The following pathologies had the greatest impact on the vital prognosis of our patients: cardiac arrhythmia, chronic kidney disease (CKD), heart failure (HF), osteoporosis, and cancer (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>, <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>).<elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="fig0005"></elsevierMultimedia>As shown in <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>/<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>, the impact of comorbidities on the survival of our outpatients diverges from that published by Divo et al.,<a class="elsevierStyleCrossRef" href="#bib0070">4</a> thus reflecting differences between both comorbidomes. In contrast to the BODE cohort, CKD and osteoporosis did show a significant relationship with mortality. We need to stress that the latter, together with HF, had the greatest impact on survival. In our cohort, ischemic heart disease and neuropsychiatric pathologies were not related to the vital prognosis of the patients.A number of works describe the negative impact of HF and CKD on COPD patients’ survival.<a class="elsevierStyleCrossRefs" href="#bib0070">4,7</a> The prevalence is even higher in overweight and obese subjects,<a class="elsevierStyleCrossRefs" href="#bib0090">8,9</a> and these account for up to 72% of our cohort. A study published by Verberne et al.<a class="elsevierStyleCrossRef" href="#bib0090">8</a> shows that, in contrast to subjects with normal weight, obese COPD patients have an increased risk of diabetes (OR 3.79, CI95% 3.04–4.71), hypertension (OR 2.46, CI95% 2.07–2.93), and HF (OR 2.32, CI95% 1.55–3.46). The authors also detected significant inverse associations between patients’ survival and anxiety disorders (OR 0.49, CI 95% 0.28–0.86) and osteoporosis (OR 0.51, CI 95% 0.37–0.71). The latter comorbidity is classically described for patients with an emphysema phenotype, usually characterized by low weight, considerable air trapping, and a worse vital prognosis than the other phenotypes.<a class="elsevierStyleCrossRef" href="#bib0100">10</a>We may not ignore the limitations of our study, i.e., the sample size, methodology—this is an observational study—and the fact that some of the comorbidities in the article by Divo et al.<a class="elsevierStyleCrossRef" href="#bib0070">4</a> were not analyzed in our cohort. In contrast to the BODE cohort, patients with relevant comorbidities that prevented them from performing the 6-minute walk test were not excluded from our study. In addition, minimum follow-up was slightly longer in our study. In this sense, our work may better represent the patients with COPD that we find in healthcare practice. This prompted us to reflect on a general applicability of the COTE index (COPD specific comorbidity test) based on the comorbidome of Divo et al.,<a class="elsevierStyleCrossRef" href="#bib0070">4</a> thinking that it should be substantiated in different patient populations. In summary, our study suggests that distributions within the comorbidome may vary according to the analyzed outpatient population." "pdfFichero" => "main.pdf" "tienePdf" => true "multimedia" => array:2 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1691 "Ancho" => 2083 "Tamanyo" => 145087 ] ] "descripcion" => array:1 [ "en" => "The “comorbidome” is a graphic expression of comorbities with more than 5% prevalence in the entire cohort. The area of the circles relates to the prevalence of the disease. The proximity to the center (mortality) express the strength of the association between the disease and the risk of death. This was scaled from the inverse of the HR (1/HR). The dotted line represents HR=1. Beyond the line, HR are less than 1. The red bubble represents statistical significance association (HR>1; P<.05). Abbreviations: HF: heart failure. CKD: chronic kidney disease. IHD: ischemic heart disease. CVA: cerebrovascular accidents. DM: diabetes mellitus. DLP: dyslipidemia. PADs: peripheral arterial disease." ] ] 1 => 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" => "Abbreviations: HF: heart failure. CKD: chronic kidney disease. IHD: ischemic heart disease. CVA: cerebrovascular accidents. SA: sleep apnea." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Comorbidities \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">Prevalence in non-deceased patients (n=308) \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">Prevalence in deceased patients (n=131) \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="2" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Hazard ratio<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> (95% confidence interval)</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">P \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">Osteoporosis, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (2.3) \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 (6.9) \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">2.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.02–3.95 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.045 \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">HF, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (9.7) \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">33 (25.2) \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">1.84 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.23–2.75 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.003 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CKD, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (9.1) \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">28 (21.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.66 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.08–2.56 \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">.020 \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">Neoplasia, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (7.8) \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">24 (18.3) \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">1.57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.00–2.44 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.049 \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">Arrhythmia, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (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">41 (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">1.51 \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">1.03–2.21 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.033 \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">Asthma, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">66 (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">33 (25.2) \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">1.43 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.96–2.13 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.078 \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">Peripheral arterial disease, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (10.1) \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">18 (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">1.12 \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">0.68–1.85 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.650 \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">Anxiety, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (7.8) \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">9 (6.9) \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">1.11 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.56–2.19 \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">.763 \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">CVA, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">21 (6.8) \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">11 (8.4) \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">1.10 \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">0.59–2.05 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.757 \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">IHD, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">45 (14.6) \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">26 (19.8) \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">1.07 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.70–1.65 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.757 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Diabetes mellitus, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">93 (30.2) \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">50 (38.2) \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">0.98 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.69–1.41 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.926 \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">SA, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">72 (23.4) \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">33 (25.2) \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">0.95 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.64–1.41 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.798 \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">Liver disease, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (8.8) \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">9 (6.9) \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">0.91 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.46–1.80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.792 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Obesity, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">97 (31.5) \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">41 (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">0.82 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.56–1.11 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.285 \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">Depression, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">42 (13.6) \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">13 (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">0.77 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.43–1.37 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.372 \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">Arterial hypertension, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">110 (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">39 (29.8) \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">0.76 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.51–1.12 \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">.170 \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">Dyslipidemia, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">99 (32.1) \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">45 (34.4) \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">0.74 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.52–1.07 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.112 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2157793.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "All the HR are estimated adjusted by age of patients." ] ] ] "descripcion" => array:1 [ "en" => "Comorbidities of COPD and their association with risk of death." ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:10 [ 0 => array:3 [ "identificador" => "bib0055" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Health care utilization in chronic obstructive pulmonary disease. 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Mikhailidis" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.2147/COPD.S119390" "Revista" => array:6 [ "tituloSerie" => "Int J Chron Obstruct Pulmon Dis" "fecha" => "2017" "volumen" => "12" "paginaInicial" => "443" "paginaFinal" => "450" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/28184156" "web" => "Medline" ] ] ] ] ] ] ] ] 7 => array:3 [ "identificador" => "bib0090" "etiqueta" => "8" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Overweight in patients with chronic obstructive pulmonary disease needs more attention: a cross-sectional study in general practice" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "L.D.M. Verberne" 1 => "C.J. Leemrijse" 2 => "I.C.S. Swinkels" 3 => "C.E. van Dijk" 4 => "D.H. de Bakker" 5 => "M.M.J. Nielen" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1038/s41533-017-0065-3" "Revista" => array:5 [ "tituloSerie" => "NPJ Prim Care Respir Med" "fecha" => "2017" "volumen" => "27" "paginaInicial" => "63" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/29167434" "web" => "Medline" ] ] ] ] ] ] ] ] 8 => array:3 [ "identificador" => "bib0095" "etiqueta" => "9" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Overweight, obesity and chronic kidney disease" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "S.M. Ting" 1 => "H. Nair" 2 => "I. Ching" 3 => "S. Taheri" 4 => "I. 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Scientific Letter

Can the COPD-comorbidome Be Applied to All Outpatients With Chronic Obstructive Pulmonary Disease? A Single-center Analysis

¿El comorbidoma de COPD se puede aplicar a todos los pacientes ambulatorios con enfermedad pulmonar obstructiva crónica? Un estudio unicéntrico

Juan Marco Figueira Gonçalvesa,

Corresponding author

juanmarcofigueira@gmail.com

Corresponding author.

, Miguel Ángel García Bellob, María Dolores Martín Martínezc, Ignacio García-Talaveraa, Rafael Golped

a Pneumology and Thoracic Surgery Service, University Hospital Nuestra Señora de la Candelaria (HUNSC), Santa Cruz de Tenerife, Spain

b Division of Clinical Epidemiology and Biostatistics, Research Unit, University Hospital Nuestra Señora de la Candelaria (HUNSC), and Primary Care Management, Santa Cruz de Tenerife, Spain

c Clinical Analysis Service, University Hospital Nuestra Señora de la Candelaria (HUNSC), Santa Cruz de Tenerife, Spain

d Respiratory Medicine Service, University Hospital Lucus Augusti, Lugo, Spain

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diabetes-associated neuropathy&#44; pulmonary fibrosis&#44; congestive heart failure&#44; gastroduodenal ulcer&#44; and anxiety were the pathologies with the greatest impact on the vital prognosis&#46; Based on these findings&#44; the group designed a bubble chart &#40;mimicking the solar system&#41; of the prevalence of these pathologies and their association with mortality and named it a &#8220;comorbidome&#8221;&#46; However&#44; distributions within this chart seem to be alterable and depend on the study population &#40;in hospital vs outpatients&#41;&#46;<a class="elsevierStyleCrossRefs" href="#bib0070"><span class="elsevierStyleSup">4&#44;5</span></a> Therefore&#44; we wondered whether the distribution of the comorbidome described by Divo et al&#46; could vary even among different outpatient populations with COPD&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">Our group has recently outlined that comorbidities&#44; particularly the cardiovascular and psychiatric ones&#44; impact the quality of life of patients with COPD &#40;measured through the COMCOLD index&#41;&#44; especially in the more symptomatic sub-groups according to the GOLD &#40;Global Initiative for Chronic Obstructive Lung Disease&#41; 2017 classification&#46;<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">6</span></a> In the present work&#44; we performed a sub-analysis of the same population&#44; aimed at reproducing the comorbidome depicted by Divo et al&#46;&#44;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">4</span></a> and evaluated &#40;1&#41; the impact of a panel of comorbidities on the survival of our outpatients with COPD and &#40;2&#41; their distribution within that comorbidome chart&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">Briefly&#44; retrospective observational study was performed on follow-up outpatients with COPD&#46; Inclusion criteria were&#58; age &#8805;40 years&#44; current or former smoker with a pack-year index &#40;PYI&#41; &#8805;10 and a forced expiratory volume in the first second &#40;FEV<span class="elsevierStyleInf">1</span>&#41;&#47;forced vital capacity &#40;FVC&#41; ratio &#60;0&#46;70 past salbutamol administration&#46; Exclusion criteria were chronic airflow obstruction and a PYI<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>10 or any pathology different from COPD&#46; Patients were stratified according to the GOLD 2017 document&#46; Information on the following comorbidities&#44; included in the Charlson comorbidity index&#44; was collected&#58; myocardial infarction&#44; angina&#44; cardiovascular disease&#44; cerebrovascular disease&#44; dementia&#44; COPD&#44; connective tissue disease&#44; gastrointestinal disease&#44; mild or severe liver disease&#44; complicated or uncomplicated diabetes mellitus&#44; stroke&#44; kidney failure&#44; cancer&#44; leukemia&#44; lymphoma&#44; secondary metastasis&#44; and AIDS&#46; Additionally evaluated pathologies were&#58; arterial hypertension&#44; dyslipidemia&#44; cardiac arrhythmia&#44; peripheral arterial disease&#44; asthma&#44; anxiety&#44; and depression&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">Qualitative variables were expressed as absolute values and percentages&#44; while quantitative variables were summarized as means<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>SD&#46; Cox logistic regression and Kaplan&#8211;Meier statistics were applied for time-dependent variables&#46; The study was approved by the Clinical Research Ethics Committee of the University Hospital Nuestra Se&#241;ora de la Candelaria &#40;Spain&#41;&#46; The comorbidome was plotted according to the original design of Divo et al&#46;&#44;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">4</span></a> where the circle diameter expressed the prevalence of the distinct comorbidities in percent and the distance of the circles to the center the risk of death based on the numerical value of the hazard ratio&#46; The comorbidome represents comorbidities with a prevalence of more than 5&#37; in the entire cohort&#46;</p><p id="par0025" class="elsevierStylePara elsevierViewall">A total of 439 patients were included in the study&#46; The cohort characteristics had been described in a previous work&#46;<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">6</span></a> The patients&#8217; mean age was 70&#59; most of them were males with a predicted FEV<span class="elsevierStyleInf">1</span>&#37; of 55<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>20&#59; 35&#37; of them were current smokers&#46; According to the GOLD 2017 categories&#44; 142 &#40;32&#37;&#41; were classified as GOLD A&#44; 207 &#40;48&#37;&#41; as GOLD B&#44; 10 &#40;2&#37;&#41; as GOLD C&#44; and 80 &#40;18&#37;&#41; as GOLD D&#46; The mean Charlson index was 2&#46;5<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>1&#46;5&#46;</p><p id="par0030" class="elsevierStylePara elsevierViewall">During the follow-up period of 53 months&#44; 131 patients &#40;30&#37;&#41; died&#46; Surviving patients were followed up for at least 41 months and a maximum of 88&#46;5 months&#46; The prevalence of comorbidities in both survivors and deceased patients is shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#46; The following pathologies had the greatest impact on the vital prognosis of our patients&#58; cardiac arrhythmia&#44; chronic kidney disease &#40;CKD&#41;&#44; heart failure &#40;HF&#41;&#44; osteoporosis&#44; and cancer &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#44; <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0035" class="elsevierStylePara elsevierViewall">As shown in <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#47;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#44; the impact of comorbidities on the survival of our outpatients diverges from that published by Divo et al&#46;&#44;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">4</span></a> thus reflecting differences between both comorbidomes&#46; In contrast to the BODE cohort&#44; CKD and osteoporosis did show a significant relationship with mortality&#46; We need to stress that the latter&#44; together with HF&#44; had the greatest impact on survival&#46; In our cohort&#44; ischemic heart disease and neuropsychiatric pathologies were not related to the vital prognosis of the patients&#46;</p><p id="par0040" class="elsevierStylePara elsevierViewall">A number of works describe the negative impact of HF and CKD on COPD patients&#8217; survival&#46;<a class="elsevierStyleCrossRefs" href="#bib0070"><span class="elsevierStyleSup">4&#44;7</span></a> The prevalence is even higher in overweight and obese subjects&#44;<a class="elsevierStyleCrossRefs" href="#bib0090"><span class="elsevierStyleSup">8&#44;9</span></a> and these account for up to 72&#37; of our cohort&#46; A study published by Verberne et al&#46;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">8</span></a> shows that&#44; in contrast to subjects with normal weight&#44; obese COPD patients have an increased risk of diabetes &#40;OR 3&#46;79&#44; CI<span class="elsevierStyleInf">95&#37;</span> 3&#46;04&#8211;4&#46;71&#41;&#44; hypertension &#40;OR 2&#46;46&#44; CI<span class="elsevierStyleInf">95&#37;</span> 2&#46;07&#8211;2&#46;93&#41;&#44; and HF &#40;OR 2&#46;32&#44; CI<span class="elsevierStyleInf">95&#37;</span> 1&#46;55&#8211;3&#46;46&#41;&#46; The authors also detected significant inverse associations between patients&#8217; survival and anxiety disorders &#40;OR 0&#46;49&#44; CI 95&#37; 0&#46;28&#8211;0&#46;86&#41; and osteoporosis &#40;OR 0&#46;51&#44; CI <span class="elsevierStyleInf">95&#37;</span> 0&#46;37&#8211;0&#46;71&#41;&#46; The latter comorbidity is classically described for patients with an emphysema phenotype&#44; usually characterized by low weight&#44; considerable air trapping&#44; and a worse vital prognosis than the other phenotypes&#46;<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">10</span></a></p><p id="par0045" class="elsevierStylePara elsevierViewall">We may not ignore the limitations of our study&#44; i&#46;e&#46;&#44; the sample size&#44; methodology&#8212;this is an observational study&#8212;and the fact that some of the comorbidities in the article by Divo et al&#46;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">4</span></a> were not analyzed in our cohort&#46; In contrast to the BODE cohort&#44; patients with relevant comorbidities that prevented them from performing the 6-minute walk test were not excluded from our study&#46; In addition&#44; minimum follow-up was slightly longer in our study&#46; In this sense&#44; our work may better represent the patients with COPD that we find in healthcare practice&#46; This prompted us to reflect on a general applicability of the COTE index &#40;COPD specific comorbidity test&#41; based on the comorbidome of Divo et al&#46;&#44;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">4</span></a> thinking that it should be substantiated in different patient populations&#46; In summary&#44; our study suggests that distributions within the comorbidome may vary according to the analyzed outpatient population&#46;</p></span>"
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          "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">The &#8220;comorbidome&#8221; is a graphic expression of comorbities with more than 5&#37; prevalence in the entire cohort&#46; The area of the circles relates to the prevalence of the disease&#46; The proximity to the center &#40;mortality&#41; express the strength of the association between the disease and the risk of death&#46; This was scaled from the inverse of the HR &#40;1&#47;HR&#41;&#46; The dotted line represents HR<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1&#46; Beyond the line&#44; HR are less than 1&#46; The red bubble represents statistical significance association &#40;HR<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>1&#59; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>&#46;05&#41;&#46; <span class="elsevierStyleItalic">Abbreviations</span>&#58; HF&#58; heart failure&#46; CKD&#58; chronic kidney disease&#46; IHD&#58; ischemic heart disease&#46; CVA&#58; cerebrovascular accidents&#46; DM&#58; diabetes mellitus&#46; DLP&#58; dyslipidemia&#46; PADs&#58; peripheral arterial disease&#46;</p>"
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          "leyenda" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleItalic">Abbreviations</span>&#58; HF&#58; heart failure&#46; CKD&#58; chronic kidney disease&#46; IHD&#58; ischemic heart disease&#46; CVA&#58; cerebrovascular accidents&#46; SA&#58; sleep apnea&#46;</p>"
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Comorbidities&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Prevalence in non-deceased patients &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>308&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Prevalence in deceased patients &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>131&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Hazard ratio<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> &#40;95&#37; confidence interval&#41;</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">P</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">Osteoporosis&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">7 &#40;2&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">9 &#40;6&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">2&#46;00&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">1&#46;02&#8211;3&#46;95&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">&#46;045&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">HF&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">30 &#40;9&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">33 &#40;25&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;84&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;23&#8211;2&#46;75&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">&#46;003&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">CKD&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">28 &#40;9&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">28 &#40;21&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;66&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;08&#8211;2&#46;56&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">&#46;020&nbsp;\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
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                  \t\t\t\t">Neoplasia&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">24 &#40;7&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">24 &#40;18&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;57&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;00&#8211;2&#46;44&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">&#46;049&nbsp;\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
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                  \t\t\t\t">Arrhythmia&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">48 &#40;15&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">41 &#40;31&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">1&#46;51&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;03&#8211;2&#46;21&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">&#46;033&nbsp;\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">Asthma&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">66 &#40;21&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">33 &#40;25&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">1&#46;43&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;96&#8211;2&#46;13&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">&#46;078&nbsp;\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">Peripheral arterial disease&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\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 &#40;10&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;650&nbsp;\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">Anxiety&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;763&nbsp;\t\t\t\t\t\t\n
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                  \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">CVA&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">&#46;757&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">IHD&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">1&#46;07&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;70&#8211;1&#46;65&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;757&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Diabetes mellitus&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">&#46;926&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">SA&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">33 &#40;25&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">0&#46;64&#8211;1&#46;41&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">&#46;798&nbsp;\t\t\t\t\t\t\n
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                  \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">Liver disease&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">&#46;792&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Obesity&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">41 &#40;31&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \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">Depression&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \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">Arterial hypertension&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">110 &#40;35&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">39 &#40;29&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">Dyslipidemia&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">99 &#40;32&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">&#46;112&nbsp;\t\t\t\t\t\t\n
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                  """
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Article information

ISSN: 15792129
Original language: English

DOI:10.1016/j.arbr.2019.10.003

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Year/Month	Html	Pdf	Total

2024 November	3	2	5
2024 October	37	17	54
2024 September	27	15	42
2024 August	65	46	111
2024 July	33	13	46
2024 June	40	18	58
2024 May	49	22	71
2024 April	36	29	65
2024 March	30	22	52
2024 February	25	24	49
2024 January	1	0	1
2023 August	1	2	3
2023 March	14	4	18
2023 February	50	13	63
2023 January	22	33	55
2022 December	51	37	88
2022 November	40	24	64
2022 October	47	35	82
2022 September	30	18	48
2022 August	39	41	80
2022 July	33	38	71
2022 June	46	27	73
2022 May	50	41	91
2022 April	79	22	101
2022 March	84	31	115
2022 February	75	28	103
2022 January	67	33	100
2021 December	46	40	86
2021 November	51	40	91
2020 April	1	0	1
2020 March	1	0	1
2019 November	1	2	3

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