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教員情報 |
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ヤベ ヒロキ 矢部 広樹 リハビリテーション学部 理学療法学科 教授 |
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■ 標題 WCN26-3595 FRAILTY SCREENING IN MAINTENANCE HEMODIALYSIS USING ROUTINELY COLLECTED DIALYSIS DATA: A MULTICENTER MACHINE LEARNING STUDY |
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■ 概要 ML models based on routinely available dialysis data can assist frailty screening in outpatient hemodialysis care. VE offered the best overall discrimination, while LR provided high recall and NPV, supporting use when missing frailty would be most harmful. Importantly, these models rely solely on data routinely collected in clinical practice, requiring no additional data acquisition. Consequently, they may enable simple, low-burden frailty screening even for busy dialysis-unit staff. Looking ahead, we will pursue external validation to confirm generalizability and to inform seamless integration into clinical workflows. Ren Takahashi, Hiroki Yabe, Hideaki Ishikawa, Takashi Hibino, Haruka Nakano, Daiki Natsume, Yoshifumi Moriyama, Tetsuya Yamada. 共著 Kidney International Reports 11(4),pp.104057 2026/04 |
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