External Validation of the Japanese Clinical Score for Mortality Prediction in Patients With Acute Heart Failure

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  • Takabayashi Kensuke
    Department of Cardiology, Hirakata Kohsai Hospital
  • Hamada Tomoyuki
    Department of Cardiology and Geriatrics, Kochi Medical School, Kochi University
  • Kubo Toru
    Department of Cardiology and Geriatrics, Kochi Medical School, Kochi University
  • Iwatsu Kotaro
    Department of Rehabilitation, Hirakata Kohsai Hospital
  • Ikeda Tsutomu
    Department of Rehabilitation, Hirakata Kohsai Hospital
  • Okada Yohei
    Department of Preventive Services, School of Public Health, Kyoto University Health Services and Systems Research, Duke-NUS Medical School, National University of Singapore
  • Kitamura Tetsuhisa
    Department of Social and Environmental Medicine, Graduate School of Medicine, Osaka University
  • Kitaguchi Shouji
    Department of Cardiology, Hirakata Kohsai Hospital
  • Kimura Takeshi
    Department of Cardiology, Hirakata Kohsai Hospital
  • Kitaoka Hiroaki
    Department of Cardiology and Geriatrics, Kochi Medical School, Kochi University
  • Nohara Ryuji
    Department of Cardiology, Takanohara Central Hospital

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<p>Background: To predict mortality in patients with acute heart failure (AHF), we created and validated an internal clinical risk score, the KICKOFF score, which takes physical and social aspects, in addition to clinical aspects, into account. In this study, we validated the prediction model externally in a different geographic area.</p><p>Methods and Results: There were 2 prospective multicenter cohorts (1,117 patients in Osaka Prefecture [KICKOFF registry]; 737 patients in Kochi Prefecture [Kochi YOSACOI study]) that had complete datasets for calculation of the KICKOFF score, which was developed by machine learning incorporating physical and social factors. The outcome measure was all-cause death over a 2-year period. Patients were separated into 3 groups: low risk (scores 0–6), moderate risk (scores 7–11), and high risk (scores 12–19). Kaplan-Meier curves clearly showed the score’s propensity to predict all-cause death, which rose independently in higher-risk groups (P<0.001) in both cohorts. After 2 years, the cumulative incidence of all-cause death was similar in the KICKOFF registry and Kochi YOSACOI study for the low-risk (4.4% vs. 5.3%, respectively), moderate-risk (25.3% vs. 22.3%, respectively), and high-risk (68.1% vs. 58.5%, respectively) groups.</p><p>Conclusions: The unique prediction score may be used in different geographic areas in Japan. The score may help doctors estimate the risk of AHF mortality, and provide information for decisions regarding heart failure treatment.</p>

収録刊行物

  • Circulation Journal

    Circulation Journal 87 (4), 543-550, 2023-03-24

    一般社団法人 日本循環器学会

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