Why the study?
Despite advances in echocardiography and biomarkers, the pathophysiological complexities among heart failure categories remain incompletely understood.
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Heart failure subtypes exhibit distinct clinical and biomarker profiles upon emergency department presentation, and subtype-specific prediction models can achieve good discrimination for in-hospital and 30-day outcomes.
INTRODUCTION: Despite advances in echocardiography and biomarkers, the pathophysiological complexities among heart failure categories remain incompletely understood. This study analyzed patients' characteristics across heart failure with reduced ejection fraction, heart failure with midrange ejection fraction, and heart failure with preserved ejection fraction presenting at the emergency department. METHODS: This is a retrospective analysis of 954 patients with acute heart failure (2016-2023) using electronic health records. Data were collected from patient triage and the emergency department and during hospitalization. Survival analysis was performed using Kaplan-Meier estimates, and an elastic net model was used to handle multicollinearity and high dimensionality in predictor variables. RESULTS: Patients (median age, 71 years) were categorized as heart failure with reduced ejection fraction (n = 363), heart failure with midrange ejection fraction (n = 131), and heart failure with preserved ejection fraction (n = 460). Patients with heart failure with preserved ejection fraction were older (80 vs 77 vs 74 years; P < .001). Heart failure with reduced ejection fraction showed higher prevalence of cardiomegaly, pleural effusion, and orthopnea (34% and 51%; P < .001), elevated diastolic blood pressure (P < .001), creatinine, N-terminal pro-B-type natriuretic peptide (P < .001), and hematocrit differences (P < .05) than heart failure with preserved ejection fraction. Echocardiographic measures differed significantly across subtypes. In-hospital prediction models achieved an area under the curve of 0.84 (91% sensitivity, 50% specificity); 30-day models had an area under the curve of 0.80 (98% sensitivity, 50% specificity). DISCUSSION: HF subtypes exhibit distinct clinical and biomarker profiles. Emergency nurses' recognition of these differences during initial assessment may enhance risk stratification and tailored interventions (eg, prioritizing diuretics in heart failure with reduced ejection fraction, managing comorbidities in heart failure with preserved ejection fraction), improving outcomes. Integrating subtype-specific data into protocols could optimize emergency department care, particularly during prolonged boarding.
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Bhattarai et al. (2025) studied this question.
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