Why the study?
Advanced heart failure is clinically heterogeneous with poor prognosis, and traditional classification systems often fail to capture the complexity required for personalized care.
Population
524 patients with advanced HF undergoing comprehensive clinical, echocardiographic, hemodynamic, and cardiopulmonary assessments
Design
Retrospective cohort study
Follow-up
Median of 2.4 years
Key result
The machine learning-derived adverse profile cluster (Cluster 2) was associated with a 3.84-fold increased risk of mortality, LVAD implantation, or heart transplantation compared to Cluster 1.
Authors
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Should not yet guide HF management; hypothesis-generating for ML phenotyping and requires prospective validation.
Cohort (n=524)
No
Effect estimate: HR 3.84 (95% CI 2.72-5.43)
Absolute Event Rate: 50% vs 15.6%
p-value: p=<0.001
Karaçam et al. (2025) conducted a cohort in Advanced heart failure (n=524). Cluster 2 (Adverse Profile Cluster) vs. Cluster 1 (Favorable Profile Cluster) was evaluated on Composite of all-cause mortality, LVAD implantation, or heart transplantation (HR 3.84, 95% CI 2.72-5.43, p=<0.001). The machine learning-derived adverse profile cluster (Cluster 2) was associated with a 3.84-fold increased risk of mortality, LVAD implantation, or heart transplantation compared to Cluster 1.
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