Pecoraro A, Andras I, Boissier R, Hevia V, Prudhomme T, Serni S, Breda A, Campi R, Territo A. The learning curve for open and minimally-invasive kidney transplantation: a systematic review.
Minerva Urol Nephrol 2022;
74:669-679. [PMID:
35622352 DOI:
10.23736/s2724-6051.22.04909-6]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
INTRODUCTION
There is lack of evidence on the impact of surgeons' learning curve on postoperative outcomes after open (OKT) or minimally-invasive (robot-assisted) kidney transplantation (RAKT). The aim of the review was to assess the learning curve (LC) for OKT and RAKT, focusing on intra-, perioperative and functional outcomes.
EVIDENCE ACQUISITION
A systematic review of the English-language literature published between 01/01/2000 - 10/12/2021 was conducted using the MEDLINE (Via PubMed), Web of Science and the Cochrane Library databases according to the principles highlighted by the EAU Guidelines Office and the PRISMA statement recommendations. The review protocol was registered on PROSPERO (CRD42022301132). The overall quality of evidence was assessed according to GRADE recommendations.
EVIDENCE SYNTHESIS
Twelve studies were included in the qualitative analysis. Surgical competence in terms of operative and re-warming times was defined after 30 cases in OKT and after 11-35 cases in RAKT. Decreased complications rates were observed after 20-33 cases in OKT and 10-30 cases in RAKT. Optimal functional outcomes were achieved after 33 cases in OKT and 15-25 cases in RAKT. However, while a poor OKT experience did not influence the LC for RAKT, lack of robotic surgery exposure could lead to a longer LC for the robotic approach.
CONCLUSIONS
OKT and RAKT appear to have similar LCs and might require about 30 cases to achieve optimal surgical and functional outcomes. Previous expertise in OKT is warranted to shorten the LC for RAKT. Further research is needed to validate these thresholds using standardized reporting metrics.
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