Development and Internal-External Validation of a Post-Operative Mortality Risk Calculator for Pediatric Surgical Patients in Low- and Middle- Income Countries Using Machine Learning.

Journal: Journal of pediatric surgery
PMID:

Abstract

BACKGROUND: The purpose of this study was to develop and validate a mortality risk algorithm for pediatric surgery patients treated at KidsOR sites in 14 low- and middle-income countries.

Authors

  • Lauren Eyler Dang
    University of California, Berkeley, School of Public Health, Division of Biostatistics, Berkeley, CA; University of California, San Francisco, Department of Surgery, San Francisco, CA.
  • Greg Klazura
    Division of Pediatric Surgery, Department of Surgery, University of Illinois Hospital and Health Sciences System, Chicago, Illinois, USA.
  • Ava Yap
    UCSF Center for Health Equity in Surgery and Anesthesia, San Francisco, CA, USA.
  • Doruk Ozgediz
    UCSF Center for Health Equity in Surgery and Anesthesia, San Francisco, CA, USA.
  • Emma Bryce
    Usher Institute of Population Health Sciences and Informatics at the University of Edinburgh, Edinburgh, Scotland, UK; KidsOR Research Team, Edinburgh, Scotland, UK.
  • Maija Cheung
    Yale University Medical Center, New Haven, CT, USA.
  • MaĆ­ra Fedatto
    KidsOR Research Team, Edinburgh, Scotland, UK.
  • Emmanuel A Ameh
    National Hospital Abuja, Abuja, Nigeria.