External validation of machine learning algorithm predicting prolonged opioid prescriptions in opioid-naïve lumbar spine surgery patients using a Taiwanese cohort.

Journal: Journal of the Formosan Medical Association = Taiwan yi zhi
PMID: 37453900

Abstract

BACKGROUND/PURPOSE: Identifying patients at risk of prolonged opioid use after surgery prompts appropriate prescription and personalized treatment plans. The Skeletal Oncology Research Group machine learning algorithm (SORG-MLA) was developed to predict the risk of prolonged opioid use in opioid-naive patients after lumbar spine surgery. However, its utility in a distinct country remains unknown.

Authors

  • Shin-Fu Chen
    Department of Orthopaedic Surgery, National Taiwan University Hospital, Taiwan; Department of Medical Education, National Taiwan University Hospital, Taiwan. Electronic address: b05401016@ntu.edu.tw.
  • Chih-Chi Su
    Department of Orthopaedic Surgery, National Taiwan University Hospital, Taiwan; Department of Medical Education, National Taiwan University Hospital, Taiwan. Electronic address: jimmysu0302@gmail.com.
  • Chuan-Ching Huang
    Department of Orthopaedic Surgery, National Taiwan University Hospital, Taipei, Taiwan.
  • Paul T Ogink
  • Hung-Kuan Yen
    School of Medicine, National Taiwan University College of Medicine, Taipei, Taiwan.
  • Olivier Q Groot
    Department of Orthopedic Surgery, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, Boston, MA 02114, USA.
  • Ming-Hsiao Hu
    Department of Orthopedics, National Taiwan University College of Medicine and National Taiwan University Hospital, Taipei, Taiwan. Electronic address: minghsiaohu@yahoo.com.tw.

Keywords

External Resources

Popular Topics
Recent Journals