Comorbidity Clusters in Acute Heart Failure: Insights From the AMERICCAASS Registry

Acute heart failure (HF) frequently coexists with multimorbidity. Comorbidity clusters have been associated with distinct clinical outcomes, but data from the Americas remain limited. We aimed to identify comorbidity clusters in patients with acute HF and assess their association with in-hospital outcomes.

This cohort study applied latent class analysis to patients from the AMERICCAASS Registry (Registro Americano de Insuficiencia Cardiaca Ambulatoria o Agudamente descompensada). Adjusted Poisson regression assessed in-hospital mortality and intensive care unit (ICU) admission, and multivariable analysis identified independent predictors of ICU admission.

Among 1638 patients, 60.6% were men and the median age was 67.2 years. Hypertension (69.4%), smoking (40.3%), and coronary artery disease (33.8%) were common comorbidities. Cluster 1 (Young, n=828) included the youngest patients (median age 63.2 years) with the fewest comorbidities. Cluster 2 (Cardio-Kidney-Metabolic, n=512) represented the oldest group (median age 71.8 years) with the highest median body mass index (27.7 kg/m²), the greatest proportion of HF with mildly reduced or preserved ejection fraction (44.7%), and a high comorbidity burden. Cluster 3 ("Ischemic," n=298) was characterized by older patients (median age 70.2 years) with an exceptionally high prevalence of coronary artery disease (96.3%) and the greatest proportion of HF with reduced ejection fraction (61.4%). ICU admission risk was higher in Cluster 2 (adjusted risk ratio [aRR], 1.15 [95% CI, 1.03-1.27]; P=0.009) and Cluster 3 (aRR, 1.25 [95% CI, 1.12-1.39]; P<0.001), compared with Cluster 1. Severe valvular insufficiency, peripheral artery disease, dyslipidemia, cancer, acute coronary syndrome, anemia, and cardiogenic shock were associated with higher ICU admission risk.

Patients with acute HF in the Americas exhibit distinct comorbidity patterns associated with different clinical profiles and ICU admission rates, which may inform risk stratification and management strategies.

URL: https://www.clinicaltrials.gov; Unique Identifier: NCT05295641.