Machine learning to risk stratify chest pain patients with non-diagnostic electrocardiogram in an Asian emergency department.

Journal: Annals of the Academy of Medicine, Singapore
PMID: 40324889

Abstract

INTRODUCTION: Elevated troponin, while essential for diagnosing myocardial infarction, can also be present in non-myocardial infarction conditions. The myocardial-ischaemic-injury-index (MI3) algorithm is a machine learning algorithm that considers age, sex and cardiac troponin I (TnI) results to risk-stratify patients for type 1 myocardial infarction.

Authors

  • Ziwei Lin
    Endocrinology and Metabolism Center, National Metabolic Management Center, Division of Metabolic Surgery for Obesity and Diabetes, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Tar Choon Aw
    Department of Laboratory Medicine, Changi General Hospital, Singapore.
  • Laurel Jackson
    Core Diagnostics, Abbott Laboratories, Lake Forest, Illinois, US.
  • Cheryl Shumin Kow
    Department of General Surgery, Singapore General Hospital, Singapore.
  • Gillian Murtagh
    Core Diagnostics, Abbott Laboratories, Lake Forest, Illinois, US.
  • Siang Jin Terrance Chua
    Department of Cardiology, National Heart Centre Singapore, Singapore.
  • Arthur Mark Richards
    Cardiovascular Research Institute, Yong Loo Lin School of Medicine, National University of Singapore.
  • Swee Han Lim
    Department of Emergency Medicine, Singapore General Hospital, Singapore.

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