Why the study?
HFpEF is rapidly increasing in Japan with distinct clinical and pathophysiological features compared to Western populations, necessitating region-specific phenotypic characterization and consensus frameworks.
Answers are grounded in this paper and cite their sources.
This position paper provides a pragmatic consensus framework of 4 distinct HFpEF phenogroups specific to the Japanese population to guide interpretation of disease heterogeneity and future phenotype-informed therapeutic research.
Heart failure with preserved ejection fraction (HFpEF) is rapidly increasing in Japan in parallel with population aging, rising from just over half of all heart failure cases in 2015 to approximately 54% in 2025 and projected to reach nearly 57% by 2040–2050. HFpEF is a multifactorial syndrome shaped by diverse clinical and pathophysiological drivers. In East Asia, where obesity is less prevalent than in Western countries, the relative contribution of these different drivers may differ, underscoring the need for region-specific phenotypic characterization. In recent years, multiple Japanese registries have reported machine learning-based phenotyping analyses in HFpEF, identifying broadly similar but not identical patient clusters. In this position paper, we provide an integrative overview of major Japanese HFpEF cohorts and synthesize these findings to propose a pragmatic consensus framework for interpreting HFpEF heterogeneity in Japan. Despite methodological differences across cohorts, several clinical domains consistently emerged, including atrial remodeling/atrial fibrillation, vascular–cardiorenal dysfunction, metabolic burden, and systemic vulnerability. Based on these shared features, we propose 4 consensus phenogroups: (1) low structural and comorbidity burden; (2) vascular and cardiorenal remodeling; (3) atrial remodeling with right heart dysfunction; and (4) systemic vulnerability. This framework may support interpretation of HFpEF heterogeneity and guide future phenotype-informed research.
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Sakata et al. (2026) conducted a review in Heart failure with preserved ejection fraction (HFpEF). Machine learning-based phenotyping was evaluated on Consensus framework of HFpEF phenogroups.
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