Added Value of Intraoperative Data for Predicting Postoperative Complications: The MySurgeryRisk PostOp Extension.

Journal: The Journal of surgical research
Published Date: Jun 9, 2020

Abstract

BACKGROUND: Models that predict postoperative complications often ignore important intraoperative events and physiological changes. This study tested the hypothesis that accuracy, discrimination, and precision in predicting postoperative complications would improve when using both preoperative and intraoperative data input data compared with preoperative data alone.

Authors

  • Shounak Datta
    Electronics and Communication Sciences Unit, Indian Statistical Institute, 203, B. T. Road, Kolkata-700 108, India. Electronic address: shounak.jaduniv@gmail.com.
  • Tyler J Loftus
    Department of Surgery, University of Florida Health, Gainesville, FL. Electronic address: tyler.loftus@surgery.ufl.edu.
  • Matthew M Ruppert
    Department of Medicine, University of Florida, Gainesville, Florida; Precision and Intelligent Systems in Medicine (Prisma(P)), University of Florida, Gainesville, Florida.
  • Chris Giordano
    Department of Anesthesiology, University of Florida, Gainesville, Florida.
  • Gilbert R Upchurch
    TCV Division, Department of Surgery, University of Virginia Medical Center, Charlottesville, Virginia.
  • Parisa Rashidi
    Department of Biomedical Engineering, University of Florida, Gainesville, FL USA.
  • Tezcan Ozrazgat-Baslanti
    Department of Medicine, University of Florida, Gainesville, FL USA.
  • Azra Bihorac
    Department of Medicine, University of Florida, Gainesville, FL USA.

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