DOI: 10.1161/jaha.126.049046 ISSN: 2047-9980

Phenotyping of Patients With Clinical Features of Advanced Heart Failure: A Latent Class Analysis of a Multicenter Registry of Patients Hospitalized With Heart Failure

Keiichi Izumi, Ryo Nakamaru, Takashi Kohno, Ayumi Goda, Yasuyuki Shiraishi, Shinsuke Takeuchi, Mitsunobu Kitamura, Yuji Nagatomo, Atsushi Mizuno, Michiru Nomoto, Munehisa Sakamoto, Kazutaka Miyamoto, Kyoko Soejima, Shun Kohsaka, Tsutomu Yoshikawa
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Background

Although the “I NEED HELP” criteria facilitate timely consideration of advanced heart failure (HF) therapies, patient classification based on the variables included in the criteria are scarcely investigated. This study aimed to identify phenotypically distinct subgroups of patients with advanced HF using unsupervised cluster analysis based on the variables included in these criteria.

Methods

A multicenter registry was used to identify patients hospitalized with HF who met at least 1 I NEED HELP criterion. Latent class analysis was performed on 9 variables from the criteria.

Results

A total of 2520 patients (mean age, 74±13 years; 40% women) were included in this study. Latent class analysis identified 3 phenotypes: more de novo HF with the lowest number of applicable criteria (phenotype 1, 31%); younger age with the lowest left ventricular ejection fraction and highest number of applicable criteria (phenotype 2, 19%); and older age with more comorbidities and poorer renal function (phenotype 3, 49%). After multivariable adjustment, phenotypes 2 and 3 were associated with a higher incidence of composite all‐cause death or rehospitalization for HF (phenotype 2: hazard ratio [HR], 1.96 [95% CI, 1.58–2.42]; phenotype 3: HR, 1.54 [95% CI, 1.28–1.84]; phenotype 1: reference) during the follow‐up period (median, 461 [interquartile range, 130–730] days).

Conclusions

This study describes a novel phenotypical classification based on the I NEED HELP criteria, with significantly different prognoses identified for patients with advanced HF. These classifications may facilitate risk stratification in this population with a complicated clinical profile.

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