The relationship between design-based lateralization, humeral bearing design, polyethylene angle, and patient-related factors on surgical complications after reverse shoulder arthroplasty: a machine learning analysis.

Journal: Journal of shoulder and elbow surgery
PMID: 38852709

Abstract

BACKGROUND: Technological advancements in implant design and surgical technique have focused on diminishing complications and optimizing performance of reverse shoulder arthroplasty (rTSA). Despite this, there remains a paucity of literature correlating prosthetic features and clinical outcomes. This investigation utilized a machine learning approach to evaluate the effect of select implant design features and patient-related factors on surgical complications after rTSA.

Authors

  • Erick M Marigi
    Department of Orthopaedic Surgery, Mayo Clinic, Jacksonville, FL, USA.
  • Jacob F Oeding
    School of Medicine, Mayo Clinic Alix School of Medicine Rochester Minnesota USA.
  • Micah Nieboer
    Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.
  • Ian M Marigi
    Washington University Medical School, St. Louis, MO, USA.
  • Brian Wahlig
    Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.
  • Jonathan D Barlow
    Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.
  • Joaquin Sanchez-Sotelo
    Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.
  • John W Sperling
    Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA. Electronic address: sperling.john@mayo.edu.

Keywords

External Resources

Popular Topics
Recent Journals