Ontology highlight
ABSTRACT: Background
Heart failure (HF) is associated with an elevated risk of morbidity, mortality, hospitalization, and impaired quality of life. One potential contributor to these poor outcomes is depression. Yet the effectiveness of treatments for depression in patients with HF is mixed, perhaps due to the heterogeneity of depression.Methods
This secondary analysis applied latent class analysis (LCA) to data from a clinical trial to classify patients with systolic HF and comorbid depression into LCA subtypes based on depression symptom severity, and then examined whether these subtypes predicted treatment response and mental and physical health outcomes at 12 months follow-up.Results
In LCA of 629 participants (mean age 63.6 ± 12.9; 43% females), we identified 4 depressio
SUBMITTER: Sadlonova M
PROVIDER: S-EPMC10523864 | biostudies-literature | 2023 Sep-Oct
REPOSITORIES: biostudies-literature