Model-based comorbidity clusters in patients with heart failure: association with clinical outcomes and healthcare utilization.

ABSTRACT:

Background

Comorbidities affect outcomes in heart failure (HF), but are not reflected in current HF classification. The aim of this study is to characterize HF groups that account for higher-order interactions between comorbidities and to investigate the association between comorbidity groups and outcomes.

Methods

Latent class analysis (LCA) was performed on 12 comorbidities from patients with HF identified from administrative claims data in the USA (OptumLabs Data Warehouse®) between 2008 and 2018. Associations with admission to hospital and mortality were assessed with Cox regression. Negative binomial regression was used to examine rates of healthcare use.

Results

In a population of 318,384 individuals, we identified five comorbidity clusters, named according to th

SUBMITTER: Gulea C 

PROVIDER: S-EPMC7812726 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature