Machine learning-based gait analysis to predict clinical frailty scale in elderly patients with heart failure.

Journal: European heart journal. Digital health
Published Date: Dec 20, 2023

Abstract

AIMS: Although frailty assessment is recommended for guiding treatment strategies and outcome prediction in elderly patients with heart failure (HF), most frailty scales are subjective, and the scores vary among raters. We sought to develop a machine learning-based automatic rating method/system/model of the clinical frailty scale (CFS) for patients with HF.

Authors

  • Yoshifumi Mizuguchi
    Department of Cardiovascular Medicine, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Kita-15 Nishi-7, Kita-ku, Sapporo 0608638, Japan.
  • Motoki Nakao
    Department of Cardiovascular Medicine, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Kita-15 Nishi-7, Kita-ku, Sapporo 0608638, Japan.
  • Toshiyuki Nagai
    Department of Cardiovascular Medicine, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Kita-15 Nishi-7, Kita-ku, Sapporo 0608638, Japan.
  • Yuki Takahashi
    Department of Cardiovascular Medicine, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Kita-15 Nishi-7, Kita-ku, Sapporo 0608638, Japan.
  • Takahiro Abe
    Department of Cardiovascular Medicine, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Kita-15 Nishi-7, Kita-ku, Sapporo 0608638, Japan.
  • Shigeo Kakinoki
    Department of Cardiology, Otaru Kyokai Hospital, Hokkaido, Japan.
  • Shogo Imagawa
    Department of Cardiology, National Hospital Organization Hakodate National Hospital, Hokkaido, Japan.
  • Kenichi Matsutani
    Department of Cardiology, Sunagawa City Medical Center, Hokkaido, Japan.
  • Takahiko Saito
    Department of Cardiology, Japan Red Cross Kitami Hospital, Hokkaido, Japan.
  • Masashige Takahashi
    Department of Cardiology, Japan Community Healthcare Organization Hokkaido Hospital, Sapporo, Japan.
  • Yoshiya Kato
    Department of Cardiology, Kushiro City General Hospital, Hokkaido, Japan.
  • Hirokazu Komoriyama
    Department of Cardiology, Kushiro City General Hospital, Hokkaido, Japan.
  • Hikaru Hagiwara
    Department of Cardiology, Kushiro City General Hospital, Hokkaido, Japan.
  • Kenji Hirata
    Department of Diagnostic Imaging, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
  • Takahiro Ogawa
    Faculty of Information Science and Technology, Hokkaido University, Sapporo, Japan.
  • Takuto Shimizu
    Technical Planning Office, INFOCOM CORPORATION, Tokyo, Japan.
  • Manabu Otsu
    Technical Planning Office, INFOCOM CORPORATION, Tokyo, Japan.
  • Kunihiro Chiyo
    Technical Planning Office, INFOCOM CORPORATION, Tokyo, Japan.
  • Toshihisa Anzai
    Department of Cardiovascular Medicine, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Kita-15 Nishi-7, Kita-ku, Sapporo 0608638, Japan.

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