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

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 diseaseObjectives. We sought to identify latent subgroups with variations regarding symptom burden, functional status, and multi-morbidity 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 num -ber of comorbidities.Results. Among 563 patients, two subgroups emerged from LCA, Class A (352 [62.5%]) and Class B (211 [37.5%]). Patients in Class A were less often classified as NYHA class III or IV (88.0% vs. 97.5%, P < 0.001), as compared to Class B patients. Class A patients had fewer symptoms, fewer comorbidities, only 25.9% had impairments in activities of daily living (ADL), and virtually none suffered from clinically significant anxiety (0.4%) or depression (0.9%). In Class B, every patient reported more than three symptoms, almost all patients (92.6%) had some impairment in ADL, and nearly a third had anxiety (30.2%) or depres-sion (28.3%). All-cause mortality after 12 months was higher in Class B, as compared to Class A (18.5% vs. 12.5%, P = 0.047).Conclusion. Among advanced HF patients, we identified a distinct subgroup characterized by a conjunction of high symptom burden, anxiety, depression, multimorbidity, and functional status impairment, which might profit particularly from palliative care interventions. J Pain Symptom Manage 2023;65:111-119.(c) 2022 American Academy of Hospice and Palliative Medicine. Pub-lished by Elsevier Inc. All rights reserved.