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Autor(en) / Beteiligte
Titel
Patient-selection algorithm for outpatient shoulder arthroplasty in ambulatory surgery center: a retrospective update
Ist Teil von
  • Journal of shoulder and elbow surgery, 2024-04, Vol.33 (4), p.900-907
Ort / Verlag
United States: Elsevier Inc
Erscheinungsjahr
2024
Quelle
ScienceDirect
Beschreibungen/Notizen
  • Outpatient total shoulder arthroplasty (TSA) presents a safe alternative to inpatient arthroplasty, while helping meet the rapidly rising volume of shoulder arthroplasty needs and minimizing health care costs. Identifying the correct patient for outpatient surgery is critical to maintaining the safety standards with TSA. This study sought to update an ambulatory surgery center (ASC) TSA patient-selection algorithm previously published by our institution. A retrospective chart review of TSAs was performed in an ASC at a single institution to collect patient demographics, perioperative risk factors, and postoperative outcomes with regard to reoperations, hospital admissions, and complications. The existing ASC algorithm for outpatient TSA was altered based on collected perioperative information, review of pertinent literature, and anesthesiology recommendations. A total of 319 TSAs were performed in an ASC in 298 patients over 7 years. Medically related complications occurred in 3 patients (0.9%) within 90 days of surgery, 2 of whom required hospital admission (0.6%) for acute kidney injury and pulmonary embolus. There were no instances of major cardiac events. Orthopedic-related complications occurred in 11 patients (3.4%), with hematoma development requiring evacuation and instability requiring revision being the most common causes. There was a low rate of perioperative complications and hospital admissions, confirming the safety of TSAs in an ASC setting. Based on prior literature and the population included, a pre-existing patient-selection algorithm was updated to better reflect increased comfort, knowledge, and data regarding safe patient selection for TSA in an ASC.
Sprache
Englisch
Identifikatoren
ISSN: 1058-2746
eISSN: 1532-6500
DOI: 10.1016/j.jse.2023.07.018
Titel-ID: cdi_proquest_miscellaneous_2857837222

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