Phenotyping of Elderly Patients With Heart Failure Focused on Noncardiac Conditions: A Latent Class Analysis From a Multicenter Registry of Patients Hospitalized With Heart Failure

Abstract

Background The burden of noncardiovascular conditions is becoming increasingly prevalent in patients with heart failure (HF). We aimed to identify novel phenogroups incorporating noncardiovascular conditions to facilitate understanding and risk stratification in elderly patients with HF. Methods and Results Data from a total of 1881 (61.2%) patients aged ≥65 years were extracted from a prospective multicenter registry of patients hospitalized for acute HF (N=3072). We constructed subgroups of patients with HF with preserved ejection fraction (HFpEF; N=826, 43.9%) and those with non-HFpEF (N=1055, 56.1%). Latent class analysis was performed in each subgroup using 17 variables focused on noncardiovascular conditions (including comorbidities, Clinical Frailty Scale, and Geriatric Nutritional Risk Index). The latent class analysis revealed 3 distinct clinical phenogroups in both HFpEF and non-HFpEF subgroups: (1) robust physical and nutritional status (Group 1: HFpEF, 41.2%; non-HFpEF, 46.0%); (2) multimorbid patients with renal impairment (Group 2: HFpEF, 40.8%; non-HFpEF, 41.9%); and (3) malnourished patients (Group 3: HFpEF, 18.0%; non-HFpEF, 12.1%). After multivariable adjustment, compared with Group 1, patients in Groups 2 and 3 had a higher risk for all-cause death over the 1-year postdischarge period (hazard ratio [HR], 2.79 [95% CI, 1.64-4.81] and HR, 2.73 [95% CI, 1.39-5.35] in HFpEF; HR, 1.96 [95% CI, 1.22-3.14] and HR, 2.97 [95% CI, 1.64-5.38] in non-HFpEF; respectively). Conclusions In elderly patients with HF, the phenomapping focused on incorporating noncardiovascular conditions identified 3 phenogroups, each representing distinct clinical outcomes, and the discrimination pattern was similar for both patients with HFpEF and non-HFpEF. This classification provides novel risk stratification and may aid in clinical decision making.

Keywords: elderly patients; heart failure; noncardiovascular conditions; phenotyping.

Figure 1. Study flowchart.

HFpEF indicates heart failure with preserved ejection fraction; and LVEF, left ventricular ejection fraction.

Figure 2. Proportion of multimorbidity, physical frailty, and malnutrition.

The percentage is in reference to the total cohort (N=1881).

Figure 3. Heat map of the phenotypic characteristics across the 3 phenogroups.

A, Non‐HFpEF. B, HFpEF. BNP indicates brain natriuretic peptide; eGFR, estimated glomerular filtration rate; GNRI, Geriatric Nutritional Risk Index; GWTG, Get With The Guidelines; HFpEF, heart failure with preserved ejection fraction; LVEF, left ventricular ejection fraction; and NT‐proBNP, N‐terminal pro‐B‐type natriuretic peptide.

Figure 4. Cumulative incidence of clinical outcomes among the 3 phenogroups.

A, Composite events. B, All‐cause death in non‐HFpEF. C, Composite events. D, All‐cause death in HFpEF. The composite event was defined as all‐cause death and heart failure readmission. HFpEF indicates heart failure with preserved ejection fraction.

Figure 5. Associations between phenogroups and clinical outcomes.

A, Non‐HFpEF. B, HFpEF. Forest plots show hazard ratios for clinical outcomes in Group 2 (systemic impairment) and Group 3 (cachexia), compared with Group 1 (robust).

Figure 6. Incidence of CVD and non‐CVD.

A, Non‐HFpEF. B, HFpEF. The cumulative incidence was estimated by the Fine‐Gray model. CVD indicates cardiovascular death.