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Prognostic value of multimodal assessment of congestion in acute heart failure
Valor pronóstico de la valoración multimodal de la congestión en la insuficiencia cardiaca aguda
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"apellidos" => "Pérez-Calvo" "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] 2 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] ] "afiliaciones" => array:4 [ 0 => array:3 [ "entidad" => "Hospital Clínico Universitario Lozano Blesa, Zaragoza, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Instituto de Investigación Sociosanitario de Aragón (IIS), Zaragoza, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Universidad de Zaragoza, Zaragoza, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Instituto Aragonés de Ciencias de la Salud (IACS), Zaragoza, Spain" "etiqueta" => "d" "identificador" => "aff0020" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Valor pronóstico de la valoración multimodal de la congestión en la insuficiencia cardiaca aguda" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 885 "Ancho" => 1513 "Tamanyo" => 73645 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0040" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">ROC curves for the various markers of congestion evaluated at the start 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">Systemic venous congestion and blood volume expansion play an important role in acute decompensated heart failure (ADHF).<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> Between 60% and 70% of patients with ADHF show signs and/or symptoms of systemic venous congestion.<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a> Despite optimal decongestive therapy, around one-third of patients are discharged with some persistent degree of clinical congestion.<a class="elsevierStyleCrossRefs" href="#bib0015"><span class="elsevierStyleSup">3,4</span></a> This condition, called residual congestion, can lead to organ dysfunction<a class="elsevierStyleCrossRefs" href="#bib0025"><span class="elsevierStyleSup">5,6</span></a> and contributes to a worse prognosis, increasing cardiovascular death and readmissions due to HF.<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a> Therefore, early detection of congestion and achieving normal blood volume as soon as possible are crucial to improving the prognosis of patients with ADHF, as indicated in the most recent HF guidelines.</p><p id="par0010" class="elsevierStylePara elsevierViewall">The detection of congestion by means of a physical examination, as described in the Framingham cohort,<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a> has been the gold standard in clinical practice for years. Furthermore, the presence of jugular vein distention or a third heart sound are independent predictors of a worse prognosis in patients with ADHF.<a class="elsevierStyleCrossRefs" href="#bib0045"><span class="elsevierStyleSup">9–12</span></a> However, some retrospective studies<a class="elsevierStyleCrossRefs" href="#bib0020"><span class="elsevierStyleSup">4,7</span></a> have demonstrated that a physical assessment of congestion is not effective in chronic HF.<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> In fact, European guidelines have recently recommended<a class="elsevierStyleCrossRefs" href="#bib0070"><span class="elsevierStyleSup">14,15</span></a> including semiquantitative methods such as lung ultrasound;<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a> bioelectrical impedance vector analysis (BIVA);<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> or the use of blood biomarkers such as N-terminal prohormone of brain natriuretic peptide (NT-proBNP),<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> cancer antigen 125 (CA125),<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> or adrenomedullin in the assessment of systemic venous congestion.<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">The aim of this study was to evaluate the usefulness of a multidimensional analysis of systemic congestion in patients hospitalized for ADHF in an internal medicine department. In these patients, comorbidities and a high prevalence of heart failure with preserved ejection fraction (HFpEF)<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a> hinder the assessment of congestion solely through physical examination.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Patients and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Objectives</span><p id="par0020" class="elsevierStylePara elsevierViewall">The primary objective of the analysis was to assess the prognostic value (all-cause mortality at 365 days) of surrogate markers of congestion upon admission (CA125, NT-proBNP, lung ultrasound, and relative plasma volume (rPV)) in patients with ADHF, evaluating the sensitivity and specificity of each marker.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Study population</span><p id="par0025" class="elsevierStylePara elsevierViewall">Between 2013 and 2018, a descriptive, noninterventional, retrospective study was conducted on 203 patients in a tertiary hospital. All patients were included following hospitalization due to ADHF and had later follow-up in an outpatient clinic exclusively dedicated to HF. The management and treatment of patients was conducted according to the criteria of the attending physicians at the aforementioned HF outpatient clinic. HF was diagnosed in accordance with the most recent European guidelines.<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a></p><p id="par0030" class="elsevierStylePara elsevierViewall">The inclusion criteria were: (1) age >18 years with a diagnosis of ADHF (both <span class="elsevierStyleItalic">de novo</span> and CHF) upon admission; (2) baseline NT-proBNP levels ≥750<span class="elsevierStyleHsp" style=""></span>pg/mL (cut-off point based on the reference laboratory); (3) comprehensive assessment of systemic venous congestion including biomarkers (NT-proBNP and CA125), lung ultrasound, inferior vena cava morphology, and rPV; (4) written informed consent for storing blood samples; and (5) follow-up in an internal medicine clinic dedicated solely to HF. The exclusion criteria were: (1) absence of any of the semiquantitative parameters studied; (2) intensive care unit admission; (3) need for renal replacement therapy; (4) significant valvular heart disease (severe aortic stenosis, severe mitral stenosis, or mitral regurgitation); (5) advanced chronic obstructive pulmonary disease (COPD) (spirometry with left ventricular ejection fraction (LVEF) <30%); and (6) ADHF due to arrhythmia (except for atrial fibrillation/flutter).</p><p id="par0035" class="elsevierStylePara elsevierViewall">LVEF was calculated according to guidelines<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">22</span></a> using a 2D echocardiogram performed during the six months prior to the admission and/or in the month following discharge once clinical stability had been achieved.</p><p id="par0040" class="elsevierStylePara elsevierViewall">The study met the fundamental guidelines of the Declaration of Helsinki and sample collection was approved by the Clinical Research Ethics Committee of Aragón (CEICA, for its initials in Spanish, Protocol Code/Investigator Code Ref. PI12/00117 dated October 3, 2012). Written informed consent was obtained from all patients who were recruited for the BIOMIC registry.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Evaluation of congestion</span><p id="par0045" class="elsevierStylePara elsevierViewall">Estimation of systemic venous congestion during hospitalization was carried out through several methods: (1) physical examination (jugular vein distention, edema, or lung crackles); (2) lung ultrasound (significant presence of Kerley B lines); (3) blood biomarkers of congestion and ventricular dysfunction (CA125 and NT-proBNP); (4) urea/creatinine ratio (U/C ratio); and (5) rPV (calculated according to hematocrit and weight).</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Surrogate markers of congestion</span><p id="par0050" class="elsevierStylePara elsevierViewall">rPV<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">23</span></a> was calculated according to the following formula: ((actual plasma volume<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>ideal plasma volume)/ideal plasma volume)<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>100. Actual plasma volume was estimated using weight (kg) and hematocrit upon admission: (1<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>hematocrit)<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>(<span class="elsevierStyleItalic">a</span><span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>(<span class="elsevierStyleItalic">b</span><span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>weight)); where “<span class="elsevierStyleItalic">a</span>” and “<span class="elsevierStyleItalic">b</span>” are constants with a value of 1530 for men and 864 for women and a value of 41 for men and 47.9 for women, respectively. Ideal plasma volume was calculated as follows: <span class="elsevierStyleItalic">c</span><span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>weight, where “<span class="elsevierStyleItalic">c</span>” is a constant with a value of 39 for men and 40 for women.</p><p id="par0055" class="elsevierStylePara elsevierViewall">The assessment of the presence of Kerley B lines was conducted upon admission<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">24</span></a> using V-SCAN and LOGIQ K6 machines (General Electric Healthcare©). Each anterior hemithorax was divided into four different areas (eight quadrants of the anterior thorax were examined). A result was considered positive when there was a simultaneous presence in both hemithorax of three or more comet tail artifacts in two different quadrants.<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">25</span></a></p><p id="par0060" class="elsevierStylePara elsevierViewall">After obtaining informed consent, the blood samples were frozen and stored at −80<span class="elsevierStyleHsp" style=""></span>°C in the BIOMIC collection (CEICA, Protocol Code/Investigator Code Ref. PI12/00117 dated October 3, 2012). Blood samples were collected for routine analysis. In regard to congestion markers, NT-proBNP<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">26</span></a> (pg/mL) (Modular Analytics Analyzer E601 Roche diagnostics GmbH, Mannheim, Germany) and CA125<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a> (U/mL) (Roche Diagnostics GmbH, Mannheim, Germany) were selected. Cystatin C<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">28</span></a> (mg/L) (N latex assay with Dade-Behring BN II GmbH, Marburg, Germany) was selected as a renal function biomarker.</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Primary outcome measure</span><p id="par0065" class="elsevierStylePara elsevierViewall">Time until the event of one-year all-cause mortality (ACM) was evaluated. Only deaths that occurred following discharge were taken into consideration. An independent investigator recorded all deaths following the index hospitalization.</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Statistical analysis</span><p id="par0070" class="elsevierStylePara elsevierViewall">Continuous variables were expressed as mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>standard deviation or median (25th percentile–75th percentile) as appropriate. Student's <span class="elsevierStyleItalic">t</span>-test (for variables with a normal distribution) and the Mann–Whitney <span class="elsevierStyleItalic">U</span> test (for variables that did not follow a normal distribution) were used to make comparisons between groups. Categorical variables were compared between groups using the Chi-square test. No imputations were made for missing values.</p><p id="par0075" class="elsevierStylePara elsevierViewall">The cut-off point for each continuous variable was selected according to the best area under the curve (AUC) on the receiver-operating characteristic (ROC) curve. The time to the event was expressed by means of Kaplan–Meier survival curves and the log-rank test was used to compare groups. Unadjusted associations between each marker of congestion (rPV, lung ultrasound, U/C ratio, NT-proBNP, and CA125) and the one-year ACM event were evaluated using univariate cause-specific Cox proportional-hazards models. For adjusted associations, multivariate cause-specific Cox proportional-hazards models were used. If the <span class="elsevierStyleItalic">p</span> value on the univariate Cox proportional-risk models was less than 20%, the candidate predictor was selected. Fractional polynomials and typification for non-normal variables were created. The backward selection procedure was chosen for the multivariate analysis.</p><p id="par0080" class="elsevierStylePara elsevierViewall">Estimates are presented with 95% confidence intervals (95% CI). Statistical significance was established as a value of <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>.05. SPSS software version 24.0 (IBM Corp., Armonk, New York) was used for the statistical analysis.</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">Baseline characteristics</span><p id="par0085" class="elsevierStylePara elsevierViewall">Once the data were processed, 203 of the 388 patients met the inclusion criteria (see Supplementary material) and were selected for the analysis. The mean age was 78.8<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.3 years and 47.3% of patients were men. More than half of the patients presented with CHF (64.4%). The most prevalent comorbidities were hypertension (86.2%), atrial fibrillation (62.2%), diabetes (42.8%), and ischemic cardiopathy (35.5%). One quarter of patients presented with advanced functional class (NYHA III or IV) upon admission and nearly 60% had HFpEF (58.6%). The prevalence of chronic kidney disease (CKD) (CKD-EPI creatinine <60<span class="elsevierStyleHsp" style=""></span>mL/min/1.73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span> prior to admission) was around 30% (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Surrogate markers of congestion</span><p id="par0090" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> shows the sensitivity (Se) and specificity (Sp) of rPV, NT-proBNP, CA125, and the U/C ratio for predicting one-year all-cause mortality. An NT-proBNP concentration greater than 3805<span class="elsevierStyleHsp" style=""></span>pg/mL showed the best AUC (0.693 [0.595–0.791]) for predicting one-year ACM (Se<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>66.7%; Sp<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>61.8%) (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>).</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0095" class="elsevierStylePara elsevierViewall">The median rPV was −3.02 (−12.05 to 5.08). Patients with a higher rPV (greater than the median) had a lower BMI, weight, and diastolic blood pressure upon admission. A greater proportion of patients were male, had a previous history of anemia (33.8% vs. 4.2%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>.001), and had a greater prevalence of lung crackles on the physical examination (78.1% vs. 59.7%). In patients with an rPV greater than the median, the baseline values of NT-proBNP (4209<span class="elsevierStyleHsp" style=""></span>pg/mL vs. 3071<span class="elsevierStyleHsp" style=""></span>pg/mL; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.071) and CA125 (58.5<span class="elsevierStyleHsp" style=""></span>U/mL vs. 40.8<span class="elsevierStyleHsp" style=""></span>U/mL; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.084) were higher, though the differences were not significant (see Supplementary material).</p><p id="par0100" class="elsevierStylePara elsevierViewall">When the rPV cut-off point was used, the survival analysis for one-year ACM came close to being significant (log-rank test<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.086) (<a class="elsevierStyleCrossRef" href="#fig0010">fig. 2</a>).</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0105" class="elsevierStylePara elsevierViewall">The median NT-proBNP concentration of all samples was 3375<span class="elsevierStyleHsp" style=""></span>pg/mL (1842–7189). Patients with higher NT-proBNP levels (above the median) tended to be elderly (>65 years), male, have a lower BMI, and have a lower systolic blood pressure upon admission. They presented with worse kidney function, as seen in the values of urea (0.50<span class="elsevierStyleHsp" style=""></span>g/dL vs. 0.60<span class="elsevierStyleHsp" style=""></span>g/dL; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.006), creatinine (1.01<span class="elsevierStyleHsp" style=""></span>mg/dL vs. 1.20<span class="elsevierStyleHsp" style=""></span>mg/dL; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>.001), and cystatin C (1.35<span class="elsevierStyleHsp" style=""></span>mg/L vs. 1.44<span class="elsevierStyleHsp" style=""></span>mg/L; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.061), as well as a greater prevalence of previous anemia (33.8% vs. 4.2%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.001). Baseline CA125 and rPV were greater in patients with NT-proBNP higher than the median (66.7<span class="elsevierStyleHsp" style=""></span>U/mL vs. 31.7<span class="elsevierStyleHsp" style=""></span>U/mL; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>.001 and −2.25% vs. −4.87%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.091, respectively) (see Supplementary material). A higher proportion of one-year ACM was found in patients with higher baseline NT-proBNP values (log-rank test<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.001), a finding which was statistically significant (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>).</p><p id="par0110" class="elsevierStylePara elsevierViewall">The median concentration of CA125 was 51.4<span class="elsevierStyleHsp" style=""></span>U/mL (22.4–113.3). Patients with higher CA125 values (greater than the median) were male, had a lower weight, and had a lower systolic blood pressure. At baseline, they also presented with a worse NYHA functional class (III or IV) as well as a high proportion of lung crackles and high serum potassium concentrations. High levels of NT-proBNP (4388<span class="elsevierStyleHsp" style=""></span>pg/mL vs. 2411<span class="elsevierStyleHsp" style=""></span>pg/mL; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>.001) were associated with higher baseline levels of CA125 (see Supplementary material). No differences associated with CA125 were found on the survival curves (log-rank test<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.563) (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>).</p><p id="par0115" class="elsevierStylePara elsevierViewall">Upon admission, 60% of patients presented with significant Kerley B lines. This group had a lower BMI, lower albumin concentrations, a more advanced NYHA functional class, and a greater proportion of lung crackles detected on a physical examination (78.1% vs. 59.7%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.017). NT-proBNP concentrations were higher (4278<span class="elsevierStyleHsp" style=""></span>pg/mL vs. 2823<span class="elsevierStyleHsp" style=""></span>pg/mL; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.004) (see Supplementary material). No differences associated with Kerley B lines were found on the survival analysis (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>).</p><p id="par0120" class="elsevierStylePara elsevierViewall">The median U/C ratio was 0.51 (0.40–0.63) (see Supplementary material). Patients who presented with a high U/C ratio (greater than the median) tended to be male and have a more advanced NYHA functional class, a greater frequency of crackles (78.1% vs. 59.7%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.017), and lower levels of NT-proBNP (2969<span class="elsevierStyleHsp" style=""></span>pg/mL vs. 4005<span class="elsevierStyleHsp" style=""></span>pg/mL; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.040). No differences associated with the U/C ratio were found on the survival analysis (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>).</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Predictors of one-year all-cause mortality</span><p id="par0125" class="elsevierStylePara elsevierViewall">During the follow-up period, 42 patients died (21.6%). Those who died had a higher mean age (82.1 years vs. 78.0 years; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.001); a lower BMI (26.8<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">2</span> vs. 28.3<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">2</span>; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.001); a more advanced NYHA functional class (48.8% vs. 18.5%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>.001); and higher concentrations of urea (0.65<span class="elsevierStyleHsp" style=""></span>g/dL vs. 0.51<span class="elsevierStyleHsp" style=""></span>g/dL; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.006), creatinine (1.22<span class="elsevierStyleHsp" style=""></span>mg/dL vs. 1.06<span class="elsevierStyleHsp" style=""></span>mg/dL; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.019), cystatin C (1.54<span class="elsevierStyleHsp" style=""></span>mg/L vs. 1.35<span class="elsevierStyleHsp" style=""></span>mg/L; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.048), CA125 (72.3<span class="elsevierStyleHsp" style=""></span>U/mL vs. 45.8<span class="elsevierStyleHsp" style=""></span>U/mL; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.037), and NT-proBNP (7442<span class="elsevierStyleHsp" style=""></span>pg/mL vs. 3071<span class="elsevierStyleHsp" style=""></span>pg/mL; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>.001) (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).</p><p id="par0130" class="elsevierStylePara elsevierViewall">According to the unadjusted Cox proportional-hazards model, the following parameters were identified as potential independent predictors of one-year ACM: age (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.006), advanced NYHA functional class (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>.001); heart rate (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.075); presence of jugular vein distention upon admission (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.090); reduced LVEF (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.061); use of mineralocorticoid receptor antagonists at the start of the study (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.094); higher values of urea (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.08), creatinine (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.043), cystatin C (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.061), rPV (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.091), and NT-proBNP concentrations (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.002); and lower values of albumin (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>.001) and hematocrit (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.014).</p><p id="par0135" class="elsevierStylePara elsevierViewall">Upon adjusting the Cox regression model (19 variables), two markers of congestion were found to be independent predictors of one-year ACM: rPV<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>−4.54% (HR 2.74 [1.18–6.38]; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.019) and NT-proBNP<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>3804 (HR 2.78 [1.27–6.08]; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.010) (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>).</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia></span></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Discussion</span><p id="par0140" class="elsevierStylePara elsevierViewall">This study consisted of a multimodal assessment of systemic venous congestion in patients with ADHF hospitalized in an internal medicine department. It provides data on the potential role these markers may play when predicting outcomes. After adjustments to the multivariate Cox proportional-hazards regression models were made, only rPV<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>−4.54% and NT-proBNP<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>3804 were identified as independent predictors of one-year ACM.</p><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Natriuretic peptides and relative plasma volume status as independent predictors of risk</span><p id="par0145" class="elsevierStylePara elsevierViewall">Relative plasma volume has previously been identified as a marker of risk in patients admitted for coronary revascularization surgery<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">29</span></a> and patients with ADHF.<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">23</span></a> This parameter can easily be calculated based on weight and hematocrit at the beginning of hospitalization and allows for estimating the degree of volume overload in patients hospitalized for ADHF. We chose a higher ROC cut-off point in our sample compared to other studies,<a class="elsevierStyleCrossRefs" href="#bib0115"><span class="elsevierStyleSup">23,29</span></a> probably due to the fact that patients included in our sample were obese (mean baseline BMI 30.3<span class="elsevierStyleHsp" style=""></span>kg/m<span class="elsevierStyleSup">2</span>) and had a high prevalence of CHF (65%), which favors water and salt retention. However, relative plasma volume should be interpreted cautiously, given that weight, which is used to calculate this variable, is not always a good marker of volume overload in patients with HF.<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">30</span></a> The use of the bioelectrical impedance vector would surely help refine these results.<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">31</span></a> In this context, Massari et al.<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">32</span></a> analyzed the prognostic value of BNP, the bioelectrical impedance vector, rPV, and the BUN/creatinine ratio in patients with ADHF and chronic HF. They developed a prognostic scoring system capable of explaining 40% of the cases of risk of death among their patients.</p><p id="par0150" class="elsevierStylePara elsevierViewall">They also identified baseline NT-proBNP as an independent predictor of one-year ACM. In the context of an increase in filling pressures, this biomarker is an indicator of ventricular wall stress. Natriuretic peptides favor natriuresis and counteract salt and water retention. On the ROC analysis, it was found that a cut-off point for NT-proBNP of 3804<span class="elsevierStyleHsp" style=""></span>pg/mL (Se<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>66.7%; Sp<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>61.8%) was the best predictor of one-year ACM. Compared to previous works,<a class="elsevierStyleCrossRefs" href="#bib0165"><span class="elsevierStyleSup">33–37</span></a> the efficacy of baseline NT-proBNP for predicting clinical outcomes was lower in our study. However, these results have to the correlated to baseline characteristics. In this regard, our sample presented with a high prevalence of CKD (nearly 30%) and more than 60% had a prior diagnosis of CHF, conditions which increase baseline NT-proBNP levels. In fact, some authors recommend adjusting NT-proBNP according to age and comorbidities at the beginning of a study, which suggests that an upper limit should be considered for predicting risk in elderly patients.<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">38</span></a></p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Potential predictive role of cancer antigen 125, lung ultrasound, and the urea/creatinine ratio in acute decompensated heart failure</span><p id="par0155" class="elsevierStylePara elsevierViewall">In our cohort, CA125, lung ultrasound, and the U/C ratio did not provide additional prognostic value for one-year ACM. The CA125 cut-off point in our analysis was lower than in other works.<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">39</span></a> This is likely due to the fact that there was a high rate of HFpEF among our patients,<a class="elsevierStyleCrossRefs" href="#bib0095"><span class="elsevierStyleSup">19,40</span></a> which could have led to an underestimation of CA125 values. Nevertheless, it has been demonstrated that CA125 provides additional prognostic value in ADHF<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">41</span></a> and in combination with other markers of congestion, such as inferior vena cava diameter at the start of the study or NT-proBNP levels, it can improve the evaluation of risk.<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">42</span></a> Our results suggest that CA125 loses its potential when all markers of congestion are simultaneously evaluated in elderly patients with ADHF.</p><p id="par0160" class="elsevierStylePara elsevierViewall">Lastly, neither lung ultrasound or the U/C ratio offered additional prognostic value in our study. The presence of a significant number of Kerley B lines in ADHF has been recognized as an independent predictor of mortality.<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">43,44</span></a> However, despite this, only 60% of patients who had a poor prognosis in our population presented with significant Kerley B lines. Comet tail artifacts are related to interstitial pulmonary edema, but are not necessarily present in patients with isolated or predominantly right-sided congestive heart failure or with low-grade pulmonary congestion, which are phenomena that tend to occur in HFpEF. Our study population mainly consisted of patients in with HFpEF which, unlike heart failure with reduced ejection fraction, is generally linked to a low degree of a systemic venous congestion.<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">45</span></a> In addition, the criteria used to define a lung ultrasound as positive at the start of the study were very strict, which could explain our results in this regard.</p><p id="par0165" class="elsevierStylePara elsevierViewall">Again, the U/C ratio offered no additional value in our analysis. A high BUN/creatinine ratio has been related to worse prognosis in ADHF.<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">43</span></a> However, it is known that this ratio is linked to age and sex, which entails a wide degree of dispersion that could explain the lack of prognostic value found in our analysis.<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">46</span></a></p></span></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Limitations</span><p id="par0170" class="elsevierStylePara elsevierViewall">First, this study is a retrospective analysis. Second, it is a single-center study. Third, the signs of congestion and lung ultrasounds were compiled by different investigators, which could have influenced the final outcome. Fourth, the lung ultrasound was recorded as a qualitative variable. The entire Kerley B lines record could have allowed us to improve the statistical analysis of this marker of congestion. Fifth, inferior vena cava diameter was measured qualitatively (<50% vs. >50%) according to each investigator's judgment.</p></span><span id="sec0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Conclusions</span><p id="par0175" class="elsevierStylePara elsevierViewall">In our sample, patients with ADHF hospitalized in the internal medicine department were elderly, had comorbidities, and had a higher prevalence of HFpEF. Depending on the physical sign examined, between 70% and 80% of patients presented with initial signs of congestion. NT-proBNP and rPV were identified as independent predictive markers of one-year ACM.</p></span><span id="sec0090" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0150">Conflicts of interest</span><p id="par0180" class="elsevierStylePara elsevierViewall">The authors declare that they do not have any conflicts of interest.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres1493204" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background" ] 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" => "xpalclavsec1355848" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1493203" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Fundamento" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Material y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1355847" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Patients and methods" "secciones" => array:6 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Objectives" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Study population" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Evaluation of congestion" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Surrogate markers of congestion" ] 4 => array:2 [ "identificador" => "sec0035" "titulo" => "Primary outcome measure" ] 5 => array:2 [ "identificador" => "sec0040" "titulo" => "Statistical analysis" ] ] ] 6 => array:3 [ "identificador" => "sec0045" "titulo" => "Results" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0050" "titulo" => "Baseline characteristics" ] 1 => array:2 [ "identificador" => "sec0055" "titulo" => "Surrogate markers of congestion" ] 2 => array:2 [ "identificador" => "sec0060" "titulo" => "Predictors of one-year all-cause mortality" ] ] ] 7 => array:3 [ "identificador" => "sec0065" "titulo" => "Discussion" "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0070" "titulo" => "Natriuretic peptides and relative plasma volume status as independent predictors of risk" ] 1 => array:2 [ "identificador" => "sec0075" "titulo" => "Potential predictive role of cancer antigen 125, lung ultrasound, and the urea/creatinine ratio in acute decompensated heart failure" ] ] ] 8 => array:2 [ "identificador" => "sec0080" "titulo" => "Limitations" ] 9 => array:2 [ "identificador" => "sec0085" "titulo" => "Conclusions" ] 10 => array:2 [ "identificador" => "sec0090" "titulo" => "Conflicts of interest" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2019-09-11" "fechaAceptado" => "2019-10-30" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1355848" "palabras" => array:5 [ 0 => "Systemic congestion" 1 => "Lung ultrasound" 2 => "NT-proBNP" 3 => "CA125" 4 => "Plasma volume status" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1355847" "palabras" => array:5 [ 0 => "Congestión sistémica" 1 => "Ecografía pulmonar" 2 => "NT-proBNP" 3 => "CA125" 4 => "Estado de volumen plasmático" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background</span><p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">A physical examination has limited performance in estimating systemic venous congestion and predicting mortality in patients with heart failure. We have evaluated the usefulness of the N-terminal prohormone of brain natriuretic peptide (NT-proBNP), cancer antigen 125 (CA125), lung ultrasound findings, relative plasma volume (rPV) estimation, and the urea/creatinine ratio as surrogate parameters of venous congestion and predictors of mortality.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">This work is a retrospective study of 203 patients admitted for acute heart failure in a tertiary hospital's internal medicine department with follow-up in a specialized outpatient clinic between 2013 and 2018. Clinical data were collected from hospital records. Treatment was decided upon according to the clinical judgment of each patient's attending physician. The main outcome measure was all-cause mortality at one year of follow-up.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Patients’ mean age was 78.8 years and 47% were male. A total of 130 (65%) patients had chronic heart failure, 51 (26.2%) patients were in New York Heart Association class III–IV, and 116 (60%) patients had preserved left ventricular ejection fraction. During follow-up, 42 (22%) patients died. Values of NT-proBNP<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>3804<span class="elsevierStyleHsp" style=""></span>pg/mL (HR 2.78 [1.27–6.08]; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.010) and rPV<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>−4.54% (HR 2.74 [1.18–6.38]; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.019) were independent predictors of all-cause mortality after one year of follow-up.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">NT-proBNP and rPV are independent predictors of one-year mortality among patients hospitalized for decompensated heart failure.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background" ] 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">Fundamento</span><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">El examen físico presenta una rentabilidad limitada en la estimación de la congestión venosa sistémica y en la predicción de la mortalidad de los pacientes con insuficiencia cardiaca. Hemos evaluado la utilidad del fragmento amino terminal del péptido natriurético cerebral (NT-proBNP), del antígeno de cáncer 125 (CA125), los hallazgos de la ecografía pulmonar, la estimación del volumen plasmático relativo (VPr) y el cociente urea/creatinina, como parámetros subrogados de congestión venosa y predictores de mortalidad.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Material y métodos</span><p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">Estudio retrospectivo de 203 pacientes ingresados por insuficiencia cardiaca aguda en el servicio de medicina interna de un hospital terciario, con seguimiento monográfico en consultas externas entre los años 2013 y 2018. Los datos clínicos se recogieron de los registros hospitalarios. Las intervenciones terapéuticas se guiaron por el criterio clínico del médico responsable de cada paciente. El desenlace principal fue mortalidad general tras un año de seguimiento.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">La edad media de los pacientes fue 78,8 años, 47% eran varones. Un total de 130 (65%) pacientes presentaban insuficiencia cardiaca crónica, 51 (26,2%) pacientes se encontraban en clase III-IV de la <span class="elsevierStyleItalic">New York Heart Association</span> y 116 (60%) pacientes presentaban fracción de eyección de ventrículo izquierdo preservada. Durante el seguimiento fallecieron 42 (22%) pacientes. Los valores de NT-proBNP<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>3.804<span class="elsevierStyleHsp" style=""></span>pg/mL (HR 2,78 [1,27-6,08]; p<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,010) y el VPr<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>–4,54% (HR 2,74 [1,18-6,38]; p<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,019) fueron predictores independientes de mortalidad general tras un año de seguimiento.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">El NT-proBNP y el VPr son predictores independientes de mortalidad a un año entre los pacientes ingresados por insuficiencia cardiaca descompensada.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Fundamento" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Material y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0010">Please cite this article as: Rubio-Gracia J, Giménez-López I, Josa-Laorden C, Sánchez-Marteles MM, Garcés-Horna V, Ruiz-Laiglesia F, et al. Valor pronóstico de la valoración multimodal de la congestión en la insuficiencia cardiaca aguda. Rev Clin Esp. 2021;221:198–206.</p>" ] ] "apendice" => array:1 [ 0 => array:1 [ "seccion" => array:1 [ 0 => array:4 [ "apendice" => "<p id="par0190" class="elsevierStylePara elsevierViewall">The following are the supplementary data to this article:<elsevierMultimedia ident="upi0005"></elsevierMultimedia></p> <p id="par0195" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="fig0015"></elsevierMultimedia></p>" "etiqueta" => "Appendix A" "titulo" => "Supplementary data" "identificador" => "sec0100" ] ] ] ] "multimedia" => array:7 [ 0 => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 885 "Ancho" => 1513 "Tamanyo" => 73645 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0040" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">ROC curves for the various markers of congestion evaluated at the start of the study.</p>" ] ] 1 => array:8 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 2259 "Ancho" => 2887 "Tamanyo" => 412078 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0045" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Survival curves for each marker of congestion for one year of all-cause mortality.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0050" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">ARB: angiotensin receptor blocker; MCRA: mineralocorticoid receptor antagonist; CA125: cancer 125 antigen; ACM: all-cause mortality; U/C ratio: urea/creatinine ratio; JVD: jugular vein distention; COPD: chronic obstructive pulmonary disease; CKD: chronic kidney disease; CKD: chronic kidney disease; AF: atrial fibrillation; HR: heart rate; LVEF: left ventricular ejection fraction; HF: heart failure; HFmrEF: heart failure with mid-range ejection fraction; HFrEF: heart failure with reduced ejection fraction; HFpEF: heart failure with preserved ejection fraction; ACEI: angiotensin-converting enzyme inhibitors; BMI: body mass index; bpm: beats per minute; SBP: systolic blood pressure; rPV: relative plasma volume.</p><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Values are expressed as mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>SD or medians (25th–75th quartiles).</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Total \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">Survivors \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">Deceased \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 \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">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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">203 (100) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" 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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">42 (21.6) \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="left" 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="elsevierStyleItalic">Age (years)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">78.8<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.3 \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">78.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.6 \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">82.1<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">.001</span> \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">BMI (kg/m</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">2</span></span><span class="elsevierStyleItalic">)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">30.3<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.4 \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28.3 (25.2–33.2) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26.8 (25.1–32.5) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.474 \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">Weight upon admission (kg)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76.6 (65.0–86.0) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76.4 (65.0–87.0) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">79.5 (65.0–82.2) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.781 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Sex, male (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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">96 (47.3) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">72 (47.4) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 (47.6) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.977 \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">Advanced NYHA class (III or IV) (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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">51 (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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27 (18.5) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 (48.8) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><.001</span> \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">SBP (mm Hg)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">140.0 (124.0–160.7) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">130.0 (121.0–155.0) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.264 \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">DBP (mm Hg)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">74.0 (65.0–84.7) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">67.0 (62.0–76.0) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">.046</span> \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">HR (bpm)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76.0 (66.0–93.0) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">80.0 (69.0–97.0) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.128 \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 " 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 " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Physical examination (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>JVD \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">135 (69.2) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">97 (66.0) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">32 (80.0) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.089 \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>Edema \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">163 (83.6) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">119 (81.0) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">36 (90.0) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.178 \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>Crackles \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">100 (69.0) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">77 (68.1) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 (73.3) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.584 \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 " 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 " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">LVEF (n [%])</span></td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.177 \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>HFpEF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">116 (58.6) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">89 (60.1) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 (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="left" 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>HFmrEF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">34 (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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26 (17.6) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (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="left" 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>HFrEF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">48 (24.2) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">33 (22.3) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15 (36.6) \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="left" 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 " 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 " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">HF-Treatment (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>Loop diuretics \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">172 (88.2) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">131 (86.8) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">37 (97.4) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.063 \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>ACEI/ARB \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">142 (72.8) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">110 (72.8) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26 (68.4) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.587 \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>Beta blockers \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">112 (57.4) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">88 (58.3) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 (52.6) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.530 \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>MRCA \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">68 (35.2) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">48 (32.0) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17 (45.9) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.111 \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 " 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 " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Comorbidities (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>Chronic HF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">130 (64.4) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">94 (61.8) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">30 (73.2) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.179 \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>Hypertension \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">175 (86.2) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">130 (86.1) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">36 (87.8) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.776 \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>Ischemic cardiopathy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">72 (35.5) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">52 (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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 (39.0) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.586 \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>Dyslipidemia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (54.5) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.793 \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>Diabetes \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">86 (42.8) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">61 (40.4) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 (48.8) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.335 \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>AF/flutter \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">125 (62.2) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">92 (60.9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29 (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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.249 \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>COPD/asthma \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">37 (18.4) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">30 (19.9) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (17.1) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.687 \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>CKD \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">56 (28.0) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">37 (24.5) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 (40.0) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.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="elsevierStyleHsp" style=""></span>Anemia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28 (19.2) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 (17.7) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (20.0) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.771 \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 " 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 " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Biochemistry</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>Urea (g/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.55 (0.42–0.73) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.51 (0.40–0.69) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.65 (0.48–0.69) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">.006</span> \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>Creatinine (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.09 (0.86–1.41) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.06 (0.84–1.39) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.22 (0.98–1.64) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">.019</span> \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>Cystatin C (mg/L) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.42 (1.11–1.61) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.35 (1.08–1.71) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.54 (1.27–1.76) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">.048</span> \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>Sodium (mmol/L) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">141.6 (139.5–144.0) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">142.0 (140.0–144.0) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">140.0 (138.2–143.8) \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="center" 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><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>Potassium (mmol/L) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.04<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.54 \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.01<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.51 \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.95<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.57 \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.319 \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>Albumin (g/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.16<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.37 \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.20<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.35 \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.99<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.43 \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">.002</span> \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>Hemoglobin (g/L) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12.1<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.8 \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>2.0 \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11.8<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.5 \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.224 \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>Hematocrit (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">37.0 (33.7–41.2) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">37.2 (33.8–42.0) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">36.1 (32.2–38.7) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.097 \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 " 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 " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Markers of congestion</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>rPV (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−3.02 (−12.0 to 5.0) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−3.93 (−12.8 to 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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−2.18 (−7.48 to 5.23) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.133 \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>CA125 (U/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">51.4 (22.4–113.3) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">45.8 (21.3–113.3) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">72.3 (33.0–161.1) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">.037</span> \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>NT-proBNP (pg/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3375 (1842–7189) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3071 (1580–6266) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7442 (2417–15,062) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><.001</span> \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>U/C ratio \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.51 (0.40–0.63) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.50 (0.40–0.62) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.50 (0.30–0.75) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.190 \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>Lung ultrasound (<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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">119 (58.6) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">86 (56.6) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28 (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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.240 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2565502.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Baseline characteristics according to all-cause mortality.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0055" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">CA125: cancer antigen 125; U/C ratio: urea/creatinine ratio; NT-proBNP: N-terminal prohormone of brain natriuretic peptide; rPV: relative plasma volume.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable \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">Cut-off point \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">Sensitivity (%) \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">Specificity (%) \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">AUC \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">CI (95%) \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">rPV (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−4.54 \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">51.2 \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.576 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.482–0.669 \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">CA125 (ng/L) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">37.05 \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">59.2 \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.605 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.508–0.702 \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">NT-proBNP (pg/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3805 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">61.8 \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.693 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.595–0.791 \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">U/C ratio \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.51 \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">53.0 \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.566 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.461–0.672 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2565503.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">ROC cut-off points of markers of congestion for all-cause mortality at the beginning of the study.</p>" ] ] 4 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0060" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Values are expressed as hazard ratio (HR) (95% CI).</p><p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">CA125: cancer 125 antigen; U/C ratio: urea/creatinine ratio; NT-proBNP: N-terminal prohormone of brain natriuretic peptide; rPV: relative plasma volume.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable \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">HR (95% CI) \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 \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">Variable \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">HR (95% CI) \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 \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">rPV<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>−4.54% \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.74 (0.92–3.31) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.091 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">rPV<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>−4.54%<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.74 (1.18–6.38) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">.019</span> \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">CA125<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>37.05 (U/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.20 (0.64–2.26) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.564 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">NT-proBNP<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>3804 (pg/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.81 (1.48–5.34) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">.002</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NT-proBNP<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>3804 (pg/mL)<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.78 (1.27–6.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">.010</span> \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">U/C ratio<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>0.51 \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.41 (0.77–2.60) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.270 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">Presence of Kerley B lines \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.48 (0.78–2.80) \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="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.234 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2565501.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Adjusted for age, history of advanced NYHA functional class, diastolic blood pressure, presence of jugular vein distention at the start of the study; left ventricular ejection fraction, history of treatment with loop diuretics, history of treatment with mineralocorticoid receptor antagonists, history of chronic heart failure, history of chronic kidney disease, Ln urea (typified), Ln creatinine (typified), Ln cystatin C (typified), Ln sodium (typified), Ln albumin (typified), Ln hematocrit (typified) (see Supplementary material).</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Unadjusted and adjusted associations on the Cox proportional-hazards regression model for one-year all-cause mortality.</p>" ] ] 5 => array:5 [ "identificador" => "upi0005" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => false "mostrarDisplay" => true "Ecomponente" => array:2 [ "fichero" => "mmc1.pdf" "ficheroTamanyo" => 165840 ] ] 6 => array:5 [ "identificador" => "fig0015" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => false "mostrarDisplay" => true "figura" => array:1 [ 0 => array:4 [ "imagen" => "mmc2.jpeg" "Alto" => 1247 "Ancho" => 2341 "Tamanyo" => 96608 ] ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:46 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Impact of systemic venous congestion in heart failure" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "M. 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