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Predictors of heart failure after acute coronary syndrome
Session:
Sessão de Posters 02 - Síndromes coronárias agudas: vias, atrasos e impacto das recomendações
Speaker:
Luis Miguel de Sousa Azevedo
Congress:
CPC 2026
Topic:
E. Coronary Artery Disease, Acute Coronary Syndromes, Acute Cardiac Care
Theme:
13. Acute Coronary Syndromes
Subtheme:
13.2 Acute Coronary Syndromes – Epidemiology, Prognosis, Outcome
Session Type:
Posters Eletrónicos
FP Number:
---
Authors:
Luís Sousa Azevedo; Isabel Martins Moreira; Isabel Nobrega Fernandes; Pedro Sousa Mateus; Silvia Leão; Ilídio Moreira
Abstract
<p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Aptos,sans-serif"><strong>Introduction</strong><br /> Ischemic heart disease is one of the leading causes of heart failure (HF) worldwide; therefore, patients presenting with acute coronary syndrome (ACS) are at particularly high risk of developing this condition</span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Aptos,sans-serif"><strong>Objective</strong><br /> To identify predictors of the occurrence of heart failure during hospital stay in patients admitted with ACS.</span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Aptos,sans-serif"><strong>Methods</strong><br /> This retrospective observational study included patients admitted to our centre with ACS between October 2010 and July 2025, all of whom were recorded in a national registry. Individuals with a previous diagnosis of HF were excluded. The cohort was divided into two groups based on whether de novo heart failure developed during the hospitalization. Differences between groups were assessed using the chi-square test for categorical variables and median-comparison tests for continuous variables. The impact of each variable on the occurrence of HF was evaluated using binary logistic regression adjusted for potential confounders. For the regression analysis, non-smokers and former smokers were combined into a single category, and unstable angina served as the reference category for ACS type.</span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Aptos,sans-serif"><strong>Results</strong><br /> A total of 1,392 patients were included, of whom 1015 (72.9%) were male, with a median age of 67 years. During hospitalization, 253 patients (17.7%) developed heart failure. Significant differences between groups were observed for gender, age, smoking status, arterial hypertension, diabetes mellitus, valvular heart disease, chronic obstructive pulmonary disease (COPD), hemoglobin at admission, and ACS type. (table 1). In the multivariable logistic regression analysis adjusted for confounders, female sex (OR = 1.554; 95% CI 1.070–2.256; p = 0.021), arterial hypertension (OR = 1.920; 95% CI 1.247–2.955; p = 0.003), diabetes mellitus (OR = 1.795; 95% CI 1.238–2.601; p = 0.002), valvular heart disease (OR = 3.582; 95% CI 1.218–10.530; p = 0.02), COPD (OR = 2.067; 95% CI 1.026–4.165; p = 0.042), and ACS type (p < 0.001) were independent predictors for heart failure. Specifically, ST-segment elevation myocardial infarction (STEMI) (OR = 17.780; 95% CI 2.403–131.550; p = 0.005) and acute myocardial infarction of unspecified location (OR = 15.030; 95% CI 1.800 – 125.516; p = 0.013) emerged as independent predictors in the ACS type category.</span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Aptos,sans-serif"><strong>Conclusions</strong></span></span></p> <p style="text-align:justify"><span style="font-size:11.0pt"><span style="font-family:"Aptos",sans-serif">In this study, female sex, arterial hypertension, diabetes mellitus, valvular heart disease, and COPD were associated with an increased likelihood of developing heart failure during hospitalization, irrespective of ACS type. Regarding ACS type, patients presenting with STEMI or myocardial infarction of unspecified location were more likely to develop this complication. These findings identify patient subgroups that may benefit from closer in-hospital monitoring to ensure timely and appropriate management</span></span></p>
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