Developing a Machine-Learning Predictive Model for Retention of Posterior Cruciate Ligament in Patients Undergoing Total Knee Arthroplasty.

Journal: Orthopaedic surgery
Published Date: May 1, 2024

Abstract

OBJECTIVE: Predicting whether the posterior cruciate ligament (PCL) should be preserved during total knee arthroplasty (TKA) procedures is a complex task in the preoperative phase. The choice to either retain or excise the PCL has a substantial effect on the surgical outcomes and biomechanical integrity of the knee joint after the operation. To enhance surgeons' ability to predict the removal and retention of the PCL in patients before TKA, we developed machine learning models. We also identified significant feature factors that contribute to accurate predictions during this process.

Authors

  • Long Chen
    Department of Critical Care Medicine, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
  • LiYi Zhang
    Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Institute of Respiratory Diseases of Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, 510630, China.
  • Diange Zhou
    Arthritis Clinical and Research Center, Peking University People's Hospital, Peking University, Beijing, China.
  • Shengjie Dong
    Orthopedic Department, Yantaishan Hospital, Yantai, China.
  • Dan Xing
    Arthritis Clinical and Research Center, Peking University People's Hospital, Peking University, Beijing, China.

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