Using Latent Class Analysis to Identify Different Clinical Profiles Among Patients With Advanced Heart Failure.

ABSTRACT:

Context

Although palliative care is guideline-indicated for patients with advanced heart failure (HF), the scarcity of a specialty-trained palliative care workforce demands better identification of patients who are most burdened by the disease.

Objectives

We sought to identify latent subgroups with variations regarding symptom burden, functional status, and multimorbidity in an advanced HF population.

Methods

We performed a latent class analysis (LCA) of baseline data from a trial enrolling advanced HF patients. As LCA input variables, we chose indicators of HF severity, physical and psychological symptom burden, functional status, and the number of comorbidities.

Results

Among 563 patients, two subgroups emerged from LCA, Class A (352 [62.5%]) and Class B (211

SUBMITTER: Blum M 

PROVIDER: S-EPMC9994448 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature