SPC365

Determinants of In-Hospital Mortality in Acute Heart Failure: A Retrospective ICU Cohort

Session: Sessão de Posters 50 - Terapêuticas avançadas na insuficiência cardíaca e em populações especiais
Speaker: Rita Ventura

Congress: CPC 2026
Topic: D. Heart Failure
Theme: 11. Acute Heart Failure
Subtheme: 11.2 Acute Heart Failure – Epidemiology, Prognosis, Outcome
Session Type: Posters Eletrónicos
FP Number: ---
Authors: Rita Ventura; Mafalda Griné; Inês Brito e Cruz; Maria João Primo; Didier Martinez; Manuel Oliveira Santos; Catarina Silva; Nuno Devesa

<p><strong>Introduction:</strong>&nbsp;Acute Heart failure (AHF) frequently complicates critical illness and remains a</p>

<p>major contributor to ICU mortality. Despite advances in monitoring and organ support, early</p>

<p>risk stratification is challenging. Identifying predictors of in-hospital mortality may help</p>

<p>clinicians recognize high-risk patients sooner.</p>

<p><strong>Purpose:&nbsp;</strong>To identify independent clinical and severity-related predictors of in-hospital</p>

<p>mortality among critically ill patients with AHF.</p>

<p><strong>Methods:&nbsp;</strong>Retrospective single-center cohort including ICU patients with decompensated HF</p>

<p>at admission or during their ICU stay (2020-2023). Clinical, laboratory, echocardiographic, and</p>

<p>treatment data were collected. Disease severity was assessed with SAPS II, APACHE II, and</p>

<p>24-hour SOFA. Candidate predictors included: left ventricular ejection fraction (LVEF)</p>

<p>category, creatinine, sodium, lactate, invasive mechanical ventilation, cardiogenic shock, renal</p>

<p>replacement therapy (RRT) and extracorporeal membrane oxygenation (ECMO). Variables</p>

<p>significant in univariate analysis were entered into a multivariable logistic regression model.</p>

<p>Model discrimination was evaluated using ROC curve analysis.</p>

<p><strong>Results:&nbsp;</strong>A total of 113 patients were included (median age 69 years; 60.5% male). In-hospital</p>

<p>mortality was 33.6% (n = 38). Non-survivors showed higher severity scores: SAPS II (61.1 &plusmn;</p>

<p>20.5 vs. 52.5 &plusmn; 17.3, p = 0.026), APACHE II (28.1 &plusmn; 9.7 vs. 23.5 &plusmn; 9.1, p = 0.019), and SOFA</p>

<p>24-hour (10.4 &plusmn; 3.2 vs. 9.0 &plusmn; 3.2, p = 0.038). Renal replacement therapy (RRT) was more</p>

<p>frequent among non-survivors (42.1% vs. 13.3%, p &lt; 0.001). Lactate was also higher (1.97</p>

<p>[1.33&mdash;4.13] vs. 1.46 [1.00&mdash;2.25], p = 0.047). Other variables - including LVEF categories,</p>

<p>creatinine, sodium, mechanical ventilation, cardiogenic shock and ECMO - were not</p>

<p>associated with mortality. In multivariable analysis, APACHE II and RRT remained</p>

<p>independent predictors: each APACHE II point increased mortality risk by 5.2% (OR = 1.05,</p>

<p>95% CI 1.00 - 1.10, p = 0.040), and RRT was associated with 4.8-fold higher odds of death</p>

<p>(OR = 4.85, 95% CI 1.85 - 12.73, p = 0.001). Model discrimination was good, with an area</p>

<p>under the ROC curve (AUC) of 0.738 (95% CI 0.63 - 0.85, p = 0.003).</p>

<p><strong>Conclusion:</strong>&nbsp;In critically ill patients with AHF, higher disease severity (APACHE II) and need</p>

<p>for RRT independently predicted in-hospital mortality. These findings highlight both the</p>

<p>prognostic relevance of early physiological severity and the impact of renal dysfunction in this</p>

<p>population.</p>

Our mission: To reduce the burden of cardiovascular disease
Visit our site

LISBOA
Campo Grande 28 - 13º |
1700-093 Lisboa
(+351) 21 797 06 85
(+351) 21 781 76 30
secretariado@spc.pt

COIMBRA
Rua de Olivença 11 - 7º Piso,
Sala 701, 3000-306 Coimbra
(+351) 239 83 81 01
(+351) 239 83 81 02
(+351) 239 83 81 03
cncdc@spc.pt

PORTO
Rua do Campo Alegre
803, Sala 8, 4150 Porto
(+351) 22 606 07 44
delegacao-norte@spc.pt