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Abstract/Summary
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<jats:title>Abstract</jats:title><jats:p>Previously, our group established a surgical gesture classification system that deconstructs robotic tissue dissection into basic surgical maneuvers. Here, we evaluate gestures by correlating the metric with surgeon experience and technical skill assessment scores in the apical dissection (AD) of robotic-assisted radical prostatectomy (RARP). Additionally, we explore the association between AD performance and early continence recovery following RARP. 78 AD surgical videos from 2016 to 2018 across two international institutions were included. Surgeons were grouped by median robotic caseload (range 80–5,800 cases): less experienced group (< 475 cases) and more experienced (≥ 475 cases). Videos were decoded with gestures and assessed using Dissection Assessment for Robotic Technique (DART). Statistical findings revealed more experienced surgeons (<jats:italic>n</jats:italic> = 10) used greater proportions of <jats:italic>cold cut</jats:italic> (<jats:italic>p</jats:italic> = 0.008) and smaller proportions of peel/push, spread, and two-hand spread (<jats:italic>p</jats:italic> < 0.05) than less experienced surgeons (<jats:italic>n</jats:italic> = 10). Correlations between gestures and technical skills assessments ranged from − 0.397 to 0.316 (<jats:italic>p</jats:italic> < 0.05). Surgeons utilizing more <jats:italic>retraction</jats:italic> gestures had lower total DART scores (<jats:italic>p</jats:italic> < 0.01), suggesting less dissection proficiency. Those who used more gestures and spent more time per gesture had lower efficiency scores (<jats:italic>p</jats:italic> < 0.01). More coagulation and hook gestures were found in cases of patients with continence recovery compared to those with ongoing incontinence (<jats:italic>p</jats:italic> < 0.04). Gestures performed during AD vary based on surgeon experience level and patient continence recovery duration. Significant correlations were demonstrated between gestures and dissection technical skills. Gestures can serve as a novel method to objectively evaluate dissection performance and anticipate outcomes.</jats:p>
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Hinweis
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DeepGreen-ID: 8f80c412b7d14884b741e3ea9860537d ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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