Learning curve analysis after 500 robotic hepatectomies

Abstract

BackgroundThe robotic platform is growing in popularity for hepatobiliary resections. Although the learning curve for basic competency has been reported, this is the first study to analyze the learning curve to achieve long-term mastery on a decade of experience with more than 500 robotic hepatectomies. MethodsAfter institutional review board approval, 500 consecutive robotic hepatectomies from 2013 to 2023 were analyzed. Cumulative sum (CUSUM) analysis using operative duration was used to determine the learning curves. ResultsA total of 500 patients were included in this study: composed of 230 men (46.0 %) and 270 women (54.0 %), aged 63.0 (61.0 ± 14.6) years, with a body mass index of 28.0 (29.0 ± 8.0) kg/m2, a Model for End-Stage Liver Disease score of 7 (8 ± 3.0), an albumin-bilirubin score of −3.0 (−3.0 ± 0.6), and a Child-Pugh score of 5.0 (5.0 ± 0.7). Operative duration was 235.0 (260.1 ± 131.9) minutes, estimated blood loss was 100.0 (165.0 ± 208.1) mL, tumor size was 4.0 (5.0 ± 3.5) cm, and 94.0 % of patients achieved R0 margins. The length of hospital stay was 3.0 (4.0 ± 3.7) days, with 4.0 % of patient having major complications. Of note, 30-day readmission was 17.0 %, 30-day mortality was 2.0 %, and 90-day mortality was 3.0 %. On CUSUM analysis, the learning curve for minor resection (n = 215) was 75 cases, major resection (n = 154) was 100 cases, and technically challenging minor resection (n = 131) was 57 cases. Gaining more experience in performing surgical procedures resulted in shorter operative duration, lower blood loss, higher R0 resections, and lower major postoperative complications. ConclusionThe minimum number of robotic hepatectomies to overcome the learning curves for mastery of minor, major, and technically challenging minor resections was significant. Our study can help guide surgeons in their early experience to optimize patient safety and outcomes.