1. Derivation and validation of a machine learning-based risk prediction model in patients with acute heart failure.
- Author
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Misumi K, Matsue Y, Nogi K, Fujimoto Y, Kagiyama N, Kasai T, Kitai T, Oishi S, Akiyama E, Suzuki S, Yamamoto M, Kida K, Okumura T, Nogi M, Ishihara S, Ueda T, Kawakami R, Saito Y, and Minamino T
- Subjects
- Humans, Risk Assessment methods, Risk Factors, Hospitalization, Machine Learning, Natriuretic Peptide, Brain, Heart Failure
- Abstract
Background: Risk stratification is important in patients with acute heart failure (AHF), and a simple risk score that accurately predicts mortality is needed. The aim of this study is to develop a user-friendly risk-prediction model using a machine-learning method., Methods: A machine-learning-based risk model using least absolute shrinkage and selection operator (LASSO) regression was developed by identifying predictors of in-hospital mortality in the derivation cohort (REALITY-AHF), and its performance was externally validated in the validation cohort (NARA-HF) and compared with two pre-existing risk models: the Get With The Guidelines risk score incorporating brain natriuretic peptide and hypochloremia (GWTG-BNP-Cl-RS) and the acute decompensated heart failure national registry risk (ADHERE)., Results: In-hospital deaths in the derivation and validation cohorts were 76 (5.1 %) and 61 (4.9 %), respectively. The risk score comprised four variables (systolic blood pressure, blood urea nitrogen, serum chloride, and C-reactive protein) and was developed according to the results of the LASSO regression weighting the coefficient for selected variables using a logistic regression model (4 V-RS). Even though 4 V-RS comprised fewer variables, in the validation cohort, it showed a higher area under the receiver operating characteristic curve (AUC) than the ADHERE risk model (AUC, 0.783 vs. 0.740; p = 0.059) and a significant improvement in net reclassification (0.359; 95 % CI, 0.10-0.67; p = 0.006). 4 V-RS performed similarly to GWTG-BNP-Cl-RS in terms of discrimination (AUC, 0.783 vs. 0.759; p = 0.426) and net reclassification (0.176; 95 % CI, -0.08-0.43; p = 0.178)., Conclusions: The 4 V-RS model comprising only four readily available data points at the time of admission performed similarly to the more complex pre-existing risk model in patients with AHF., Competing Interests: Declaration of competing interest Dr. Yuya Matsue is affiliated to a department endowed by Philips Respironics, ResMed, Teijin Home Healthcare, and Fukuda Denshi and received an honorarium from Otsuka Pharmaceutical Co and Novartis Japan. Dr. Keisuke Kida received honorariums from Daichi Sankyo Co., Ono Pharmaceutical Co., Ltd., AstraZeneca K.K., Otsuka Pharmaceutical Co., Ltd., and Novartis Pharmaceuticals Co., Ltd. Dr. Takahiro Okumura received research honoraria from Ono Yakuhin, Otsuka, Novartis, and Astrazeneca and research grants from Ono Yakuhin, Amgen Astellas, Pfizer, Alnylam, and Alexion (not in connection with the submitted work). Dr. Yoshihiko Saito received research funds from Otsuka Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co., Ltd., Mitsubishi Tanabe Pharma Corporation, Actelion Pharmaceuticals Japan Ltd., Kyowa Kirin Co., Ltd., Dainippon Sumitomo Pharma Co., Ltd., Chugai Pharmaceutical Co., Ltd., Nihon Medi-Physics Co., Ltd., Fuji Yakuhin Co., Ltd.; research expences from Roche Diagnostics K.K., Otsuka Pharmaceutical Co., Ltd., Terumo Corporation, Kowa Company, Abbott Medical Japan LLC, Alnylam Japan K.K. Cmic Holdings Co., Ltd.; Speakers' bureau/honorarium from Alnylam Japan K.K., AstraZeneca K.K., Amicus Therapeutics, Inc., Amgen K.K. Edwards Lifesciences Corporation, Otsuka Pharmaceutical Co., Ltd., Ono Pharmaceutical Co., Ltd., Kyowa Kirin Co., Ltd., Kowa Pharmaceutical Co., Ltd., Daiichi Sankyo Co., Ltd., Mitsubishi Tanabe Pharma Corporation, Tsumura & Co., Toa Eiyo Ltd., Nippon Shinyaku Co., Ltd., Nippon Boehringer Ingelheim Co., Ltd., Novartis Pharma K.K., Bayer Yakuhin Ltd., Mochida Pharmaceutical Co., Ltd., Janssen Pharmaceutical K.K.; Consultation fees from AstraZeneca K.K., Novartis Pharma K.K., Nippon Boehringer Ingelheim Co., Ltd.; Other remuneration (supervisor) from Towa Pharmaceutical Co., Ltd. The other authors have nothing to declare., (Copyright © 2023 Elsevier Ltd. All rights reserved.)
- Published
- 2023
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