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Published on: February 7, 2025
Towards identifying a learning curve for robotic abdominal wall reconstruction: a cumulative sum analysis
1Division of Gastrointestinal Surgery, Department of Surgery, University of Alabama at Birmingham, 1808 7th Avenue South, Boshell Diabetes Building #525, Birmingham, AL, 35294, USA.
Introduction:
Over the past decade, an increase has been seen in robotics used for hernia repair, specifically robotic abdominal wall reconstruction (rAWR). However, the learning curve for rAWR can be steep and presently, little is understood regarding the optimal case volume required to achieve proficiency. The aim of our study was to review skill acquisition and describe the learning curve for rAWR.
Methods:
A retrospective, single-surgeon case series of consecutive patients who underwent rAWR from 2018 to 2022. The primary outcome was operative time, obtained from console time identified through the MyIntutive application. A one-sided cumulative sum analysis (CUSUM) curve for the total operative time was derived based on the mean operative time of chronological procedures (207 min).
Results:
185 patients underwent rAWR between 2018 and 2022. These patients were more likely to be female, Caucasian, and have undergone two previous hernia repairs. ASA complexity increased over time with ASA 3 being predominant from 2020 onwards. The median hernia length was 15.0 cm and the median width was 7 cm. Average operative time was 207.8 min and decreased over time. The CUSUM analysis identified four phases of skill acquisition with the following case volumes: Initial Learning Curve (0-20), Stabilization Phase (21-55), Second Learning Curve (56-70), 4) Skill Proficiency (> 70).
Conclusion:
In the early learning curve of rAWR, operative time decreased consistently after 70 cases, with an initial inflection after 20 cases. We identified varying stages of skill acquisition that are likely typical of a surgeon as they would progress through the learning curve of advanced robotic surgery. Future studies are needed to confirm the optimal case volume for determining the skill level for the performance of rAWR.
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