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Robotic performance metrics model fellow proficiency in living donor nephrectomy

Journal of Robotic Surgery, ISSN: 1863-2491, Vol: 18, Issue: 1, Page: 271
2024
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    • News Mentions
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Most Recent News

Recent Findings from Washington University Has Provided New Information about Nephrectomy (Robotic Performance Metrics Model Fellow Proficiency In Living Donor Nephrectomy)

2024 JUL 25 (NewsRx) -- By a News Reporter-Staff News Editor at NewsRx Medical Devices Daily -- Investigators publish new report on Surgery - Nephrectomy.

Article Description

We investigated the use of robotic objective performance metrics (OPM) to predict number of cases to proficiency and independence among abdominal transplant fellows performing robot-assisted donor nephrectomy (RDN). 101 RDNs were performed by 5 transplant fellows from September 2020 to October 2023. OPM included fellow percent active control time (%ACT) and handoff counts (HC). Proficiency was defined as ACT ≥ 80% and HC ≤ 2, and independence as ACT ≥ 99% and HC ≤ 1. Case number was significantly associated with increasing fellow %ACT, with proficiency estimated at 14 cases and independence at 32 cases (R = 0.56, p < 0.001). Similarly, case number was significantly associated with decreasing HC, with proficiency at 18 cases and independence at 33 cases (R = 0.29, p < 0.001). Case number was not associated with total active console time (p = 0.91). Patient demographics, operative characteristics, and outcomes were not associated with OPM, except for donor estimated blood loss (EBL), which positively correlated with HC. Abdominal transplant fellows demonstrated proficiency at 14–18 cases and independence at 32–33 cases. Total active console time remained unchanged, suggesting that increasing fellow autonomy does not impede operative efficiency. These findings may serve as a benchmark for training abdominal transplant surgery fellows independently and safely in RDN.

Bibliographic Details

Davidson, Jesse T; Clanahan, Julie M; Kiani, Amen; Vachharajani, Neeta; Yu, Jennifer; Martens, Gregory R; Cullinan, Darren R; Hill, Angela L; Olumba, Franklin; Matson, Sarah C; Scherer, Meranda D; Doyle, Maria B Majella; Wellen, Jason R; Khan, Adeel S

Springer Science and Business Media LLC

Medicine

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