Predicting Early Hospital Discharge Following Revision Total Hip Arthroplasty: An Analysis of a Large National Database Using Machine Learning.

Journal: The Journal of arthroplasty
Published Date: Dec 9, 2024

Abstract

BACKGROUND: Revision total hip arthroplasty (rTHA) was recently removed from the Medicare inpatient-only list. However, appropriate candidate selection for outpatient rTHA remains paramount. The purpose of this study was to evaluate the utility of a large national database using machine learning (ML) and traditional multivariable logistic regression (MLR) models in predicting early hospital discharge (EHD) (< 24 hours) following rTHA. Furthermore, this study aimed to use the trained ML models, cross-referenced with traditional MLR, to determine key perioperative variables predictive of EHD following rTHA.

Authors

  • Teja Yeramosu
    Virginia Commonwealth University School of Medicine, Richmond, Virginia, U.S.A.
  • Jacob M Farrar
    Department of Orthopaedic Surgery, Virginia Commonwealth University, Richmond, Virginia.
  • Avni Malik
    College of Arts and Sciences, University of Virginia, Charlottesville, Virginia, United States of America.
  • Jibanananda Satpathy
    Department of Orthopaedic Surgery, Virginia Commonwealth University, Richmond, Virginia.
  • Gregory J Golladay
    Department of Orthopaedic Surgery, Virginia Commonwealth University, Richmond, Virginia.
  • Nirav K Patel
    Department of Orthopaedic Surgery, Johns Hopkins University, Baltimore, Maryland.

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