Heart failure monitoring with a single‑lead electrocardiogram at home.

Journal: International journal of cardiology
PMID: 40280823

Abstract

BACKGROUND: Repeated hospitalization due to heart failure (HF) is a significant predictor of mortality. However, there are limited early detection systems for HF progression that can be utilized by patients at home without a cardiac implantable electrical device (CIED). This study aimed to develop an artificial intelligence (AI)-based system utilizing convolutional neural network (CNN) algorithms for the early detection of HF progression using single‑lead electrocardiograms (ECGs), including those obtained from wearable devices such as the Apple Watch®.

Authors

  • Eriko Hasumi
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Japan. Electronic address: ehasumi-circ@umin.ac.jp.
  • Katsuhito Fujiu
    Department of Cardiovascular Medicine, The University of Tokyo.
  • Ying Chen
    Department of Endocrinology and Metabolism, Fudan Institute of Metabolic Diseases, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Sumie Miyamoto
    Department of Advanced Cardiology, Graduate School of Medicine, The University of Tokyo, Japan.
  • Mitsunori Oida
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Japan.
  • Yu Shimizu
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Japan.
  • Kunihiro Kani
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Japan.
  • Kohsaku Goto
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Japan.
  • Ryoko Uchida
    Department of Advanced Cardiology, Graduate School of Medicine, The University of Tokyo, Japan.
  • Yuxiang Liu
    National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; School of Physics and Technology, Wuhan University, Wuhan, China.
  • Tsukasa Oshima
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Japan.
  • Jun Matsuda
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Japan.
  • Takumi J Matsubara
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Japan.
  • Junichi Sugita
    Department of Hematology, Hokkaido University Hospital, Hokkaido, Japan.
  • Yukiteru Nakayama
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Japan.
  • Gaku Oguri
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Japan.
  • Toshiya Kojima
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Japan.
  • Yujin Maru
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Japan; Department of Cardiovascular Medicine, Nippon Medical School, Tokyo, Japan.
  • Satoshi Kodera
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo.
  • Hiroshi Akazawa
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo.
  • Morio Shoda
    Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Japan; Clinical Research Division for Heart Rhythm Management, Department of Cardiology, Tokyo Women's Medical University, Tokyo, Japan.
  • Issei Komuro
    Department of Cardiovascular Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.

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