ArticleJournal of robotic surgery2026
Learning curves of surgeon performance and team workflow during the first 100 hugo robotic-assisted small bowel length shortening with sleeve gastrectomy procedures.
Article in Journal of robotic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
Evidence on Hugo RAS in bariatric surgery remains limited. We evaluated the first 100 Hugo RAS small bowel length shortening with sleeve gastrectomy (BOS-SG) procedures to determine whether surgeon-level technical performance (console time) and team-level workflow (docking time) evolved differently during implementation. This retrospective single-center cohort included consecutive cases performed between February 11 and July 30, 2025. Change points were assessed using segmented linear regression, Davies tests, 95% confidence intervals, and descriptive cumulative sum (CUSUM) analysis. Early and late phases were defined by the rounded docking-time breakpoint, the most stable interpretable workflow transition. Among 100 cases, median console time was 16.0 min (interquartile range [IQR], 15.0-21.2) and docking time was 5.0 min (IQR, 3.0-5.2). CUSUM peaks occurred at cases 24 and 28, respectively. Segmented regression identified a docking-time breakpoint at case 33.1 (95% CI, 26.2-40.0; Davies p < 0.001); the console-time segmented solution was early and was not retained. From early to late phase, console time decreased from 23.0 to 16.0 min (p < 0.001), docking time from 6.0 to 4.0 min descriptively, and total operative time from 95.0 to 77.0 min (p < 0.001). Complications occurred in 1/33 and 7/67 cases (p = 0.265). Hugo RAS BOS-SG implementation showed distinct, complementary learning trajectories. Docking time, a team-workflow metric, demonstrated the most stable transition around 30-40 cases, whereas console performance improved without a stable mid-series breakpoint. Console and docking time should be treated as noninterchangeable endpoints for platform adoption.
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