Machine learning approaches for predicting prolonged hospital length of stay after lumbar fusion surgery in patients aged 75 years and older: a retrospective cohort study based on comprehensive geriatric assessment.

Journal: Neurosurgical focus
Published Date: Jul 1, 2025

Abstract

OBJECTIVE: Postoperative recovery following lumbar fusion surgery in patients aged 75 years and older often requires a prolonged length of stay (PLOS) in the hospital. Accurately predicting the risk of PLOS and assessing its risk factors for preoperative optimization are crucial to guide clinical decision-making. The aim of this study was to select the risk factors for PLOS and develop a machine learning (ML) model to estimate the likelihood of PLOS based on comprehensive geriatric assessment (CGA) domains in older patients undergoing lumbar fusion surgery.

Authors

  • Qijun Wang
    Department of Orthopedics & Elderly Spinal Surgery, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China.
  • Shuaikang Wang
  • Peng Wang
    Neuroengineering Laboratory, School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.
  • Shibao Lu
    Department of Orthopedics & Elderly Spinal Surgery, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China.

Keywords

External Resources

Popular Topics
Recent Journals