The learning curve for robotic living donor right hepatectomy: Analysis of outcomes in 2 specialized centers

Robotic surgery is an emerging minimally invasive option for living donor hepatectomy. Currently, there are no studies on the learning curve of robotic donor hepatectomy. Thus, we evaluated the learning curve for robotic donor right hepatectomy. We retrospectively reviewed prospectively collected data from consecutive living donors who underwent robotic hepatectomy at 2 specialized centers between 2016 and 2022. We estimated the number of cases required to achieve stable operating times for robotic donor right hepatectomy using cumulative sum (CUSUM) analysis. The complication rates were similar between the 2 centers (22.8% vs. 26.7%; p = 0.74). Most complications were graded as minor (70.4%). Analysis of the total operative time demonstrated that the learning curves reached a peak at the 17th case in center 1 and the 9th case in center 2. The average operation times for cases 1-17 versus 18-99 in center 1 were 603 versus 438 minutes ( p < 0.001), and cases 1-9 versus 10-15 in center 2 were 532 versus 418 minutes ( p = 0.002). Complication rates were lower after the learning curves were achieved, although this did not reach statistical significance. A comparison of outcomes between centers suggests that a standardized approach to this complex operation can be successfully transferred.

Authors

Institutions

Publication Details

Journal
Liver Transplantation
Published
2024-10-23
DOI
https://doi.org/10.1097/lvt.0000000000000480
Citations
13
Primary Topic
Hepatocellular Carcinoma Treatment and Prognosis
Type
article
Field-Weighted Citation Impact
4.80
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The learning curve for robotic living donor right hepatectomy: Analysis of outcomes in 2 specialized centers

A. Osama Gaber, Ashton A. Connor, Caroline J. Simon, Maureen A. Tellier et al.
13 citations
Liver Transplantation
Hepatocellular Carcinoma Treatment and Prognosis
4.80
article

The learning curve for robotic living donor right hepatectomy: Analysis of outcomes in 2 specialized centers

A. Osama Gaber, Ashton A. Connor, Caroline J. Simon, Maureen A. Tellier, R. Mark Ghobrial, Mohamed Akoad, Hye Yeon Yang, Elizabeth W. Brombosz, Gi Hong Choi, Dai Hoon Han, Yee Lee Cheah, Jae Kwang Kim, Despoina Daskalaki
article en
13 citations

Abstract

Robotic surgery is an emerging minimally invasive option for living donor hepatectomy. Currently, there are no studies on the learning curve of robotic donor hepatectomy. Thus, we evaluated the learning curve for robotic donor right hepatectomy. We retrospectively reviewed prospectively collected data from consecutive living donors who underwent robotic hepatectomy at 2 specialized centers between 2016 and 2022. We estimated the number of cases required to achieve stable operating times for robotic donor right hepatectomy using cumulative sum (CUSUM) analysis. The complication rates were similar between the 2 centers (22.8% vs. 26.7%; p = 0.74). Most complications were graded as minor (70.4%). Analysis of the total operative time demonstrated that the learning curves reached a peak at the 17th case in center 1 and the 9th case in center 2. The average operation times for cases 1-17 versus 18-99 in center 1 were 603 versus 438 minutes ( p < 0.001), and cases 1-9 versus 10-15 in center 2 were 532 versus 418 minutes ( p = 0.002). Complication rates were lower after the learning curves were achieved, although this did not reach statistical significance. A comparison of outcomes between centers suggests that a standardized approach to this complex operation can be successfully transferred.

Liver TransplantationVol. 31(2)
Cleveland Clinic (US), Yonsei University (KR), Cornell University (US), Lahey Medical Center (US), Methodist Hospital (US), Ajou University (KR)
Openalex Percentile: Top 4%
Hepatocellular Carcinoma Treatment and Prognosis
4.80
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.