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

Author:

Nakamaru Ryo12ORCID,Shiraishi Yasuyuki1,Niimi Nozomi1,Kohno Takashi3ORCID,Nagatomo Yuji4ORCID,Takei Makoto5ORCID,Ikoma Takenori6ORCID,Nishikawa Kei7,Sakamoto Munehisa8ORCID,Nakano Shintaro9ORCID,Kohsaka Shun1ORCID,Yoshikawa Tsutomu7

Affiliation:

1. Department of Cardiology Keio University School of Medicine Tokyo Japan

2. Department of Healthcare Quality Assessment The University of Tokyo Tokyo Japan

3. Department of Cardiovascular Medicine Kyorin University Faculty of Medicine Tokyo Japan

4. Department of Cardiology, National Defense Medical College Tokorozawa Japan

5. Department of Cardiology Saiseikai Central Hospital Tokyo Japan

6. Division of Cardiology, Internal Medicine III Hamamatsu University School of Medicine Hamamatsu Japan

7. Department of Cardiology Sakakibara Heart Institute Tokyo Japan

8. Department of Cardiology National Hospital Organization Tokyo Medical Center Tokyo Japan

9. Department of Cardiology Saitama Medical University, International Medical Center Hidaka Japan

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.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Cardiology and Cardiovascular Medicine

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