Machine learning-based prediction of elevated N terminal pro brain natriuretic peptide among US general population.

Journal: ESC heart failure
PMID: 39558857

Abstract

AIMS: Natriuretic peptide-based pre-heart failure screening has been proposed in recent guidelines. However, an effective strategy to identify screening targets from the general population, more than half of which are at risk for heart failure or pre-heart failure, has not been well established. This study evaluated the performance of machine learning prediction models for predicting elevated N terminal pro brain natriuretic peptide (NT-proBNP) levels in the US general population.

Authors

  • Yuichiro Mori
    Department of Radiology, Kagawa University Hospital.
  • Shingo Fukuma
    Human Health Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan.
  • Kyohei Yamaji
    Department of Cardiovascular Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Atsushi Mizuno
    Department of Cardiovascular Medicine, St. Luke's International Hospital, Tokyo, Japan.
  • Naoki Kondo
    Department of Social Epidemiology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Kosuke Inoue
    Department of Social Epidemiology, Graduate School of Medicine, Kyoto University, Sakyo, Kyoto, Japan.

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