Phenogrouping heart failure with preserved or mildly reduced ejection fraction using electronic health record data.

ABSTRACT:

Background

Heart failure (HF) with preserved or mildly reduced ejection fraction includes a heterogenous group of patients. Reclassification into distinct phenogroups to enable targeted interventions is a priority. This study aimed to identify distinct phenogroups, and compare phenogroup characteristics and outcomes, from electronic health record data.

Methods

2,187 patients admitted to five UK hospitals with a diagnosis of HF and a left ventricular ejection fraction ≥ 40% were identified from the NIHR Health Informatics Collaborative database. Partition-based, model-based, and density-based machine learning clustering techniques were applied. Cox Proportional Hazards and Fine-Gray competing risks models were used to compare outcomes (all-cause mortality and hospitalisation

SUBMITTER: Soltani F 

PROVIDER: S-EPMC11229019 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature