Machine-learning models for the prediction of ideal surgical outcomes in patients with adult spinal deformity.

Journal: The bone & joint journal
PMID: 40020727

Abstract

AIMS: Adult spinal deformity (ASD) surgery can reduce pain and disability. However, the actual surgical efficacy of ASD in doing so is far from desirable, with frequent complications and limited improvement in quality of life. The accurate prediction of surgical outcome is crucial to the process of clinical decision-making. Consequently, the aim of this study was to develop and validate a model for predicting an ideal surgical outcome (ISO) two years after ASD surgery.

Authors

  • Dongfan Wang
    Department of Orthopedics & Elderly Spinal Surgery, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China.
  • Qijun Wang
    Department of Orthopedics & Elderly Spinal Surgery, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China.
  • Peng Cui
    School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Rd., Minhang, Shanghai 200240. China.
  • Shuaikang Wang
  • Di Han
  • Xiaolong Chen
    Department of Orthopedics & Elderly Spinal Surgery, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China.
  • Shibao Lu
    Department of Orthopedics & Elderly Spinal Surgery, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China.

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