ArticleJournal of robotic surgery2026
Initial adaptation to robotic rectal cancer surgery using the hinotori surgical robot system: a CUSUM analysis of certified proctor surgeons.
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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11 authors.
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Abstract
The early adaptation process after transition to a new robotic platform for rectal cancer surgery remains unclear. This single-center retrospective exploratory study compared time-based adaptation patterns in hinotori-assisted rectal cancer surgery between two certified proctor surgeons with different prior da Vinci experience. Fifty-five hinotori-assisted anterior resections with double-stapling technique anastomosis performed by two predefined institutional lead surgeons were analyzed. Both were certified robotic colorectal surgery proctors and had obtained da Vinci proctor certification before the study; they subsequently obtained hinotori proctor certification during the study period. Before the introduction of hinotori, Surgeon A and Surgeon B performed 262 and 90 da Vinci-assisted rectal cancer procedures, respectively. Total operative time, cockpit time, and setup time were evaluated chronologically using a simple cumulative sum (CUSUM) analysis and interpreted descriptively rather than as proficiency thresholds. Surgeon A performed 26 cases, and Surgeon B performed 29. Surgeon A showed a setup-time transition at case 11, decreasing from 29.5 to 17.6 min, whereas total operative time and cockpit time showed multiphasic patterns. Surgeon B showed sequential transitions in setup time, cockpit time, and total operative time at cases 10, 13, and 22, respectively. No CRM/RM positivity, conversion, or platform-specific adverse events occurred. Different initial adaptation patterns were observed during transition to the hinotori platform between two certified robotic surgeons with differing prior da Vinci-assisted rectal cancer surgery volumes. Prior robotic experience, case complexity, team adaptation, and platform-specific workflow should be considered when interpreting early outcomes after transition to a new robotic platform.
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