Mp41-01 dissection assessment for robotic technique (dart) to evaluate nerve-spare of robot-assisted radical prostatectomy

You have accessJournal of UrologyCME1 May 2022MP41-01 DISSECTION ASSESSMENT FOR ROBOTIC TECHNIQUE (DART) TO EVALUATE NERVE-SPARE OF ROBOT-ASSISTED RADICAL PROSTATECTOMY Runzhuo Ma, Alvin Hui, Jiashu Xu, Aditya Desai, Michael Tzeng, Emily Cheng, Loc Trinh, Jessica H. Nguyen, Anima Anandkumar, Jim C. Hu, and Andrew J. Hung Runzhuo MaRunzhuo Ma More articles by this author , Alvin HuiAlvin Hui More articles by this author , Jiashu XuJiashu Xu More articles by this author , Aditya DesaiAditya Desai More articles by this author , Michael TzengMichael Tzeng More articles by this author , Emily ChengEmily Cheng More articles by this author , Loc TrinhLoc Trinh More articles by this author , Jessica H. NguyenJessica H. Nguyen More articles by this author , Anima AnandkumarAnima Anandkumar More articles by this author , Jim C. HuJim C. Hu More articles by this author , and Andrew J. HungAndrew J. Hung More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002607.01AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: High quality nerve-spare (NS) is essential for the preservation of erectile function (EF) after robot-assisted radical prostatectomy (RARP). In a previous study, we developed an assessment tool for tissue dissection, Dissection Assessment for Robotic Technique (DART). Herein, we further apply DART scores to the NS step and evaluate whether DART can predict 1-year EF recovery after RARP. METHODS: RARP cases from 2016-2019 with preoperative EF and ≥1 year postoperative follow up were included. Non-nerve-sparing procedures were excluded. Phase 1: After standardized training, 5 independent assessors used DART to evaluate de-identified NS videos. Inter-rater reliability (IRR) was evaluated by prevalence-adjusted and bias-adjusted Kappa (PABAK). DART scores of surgeons with different experience levels were compared by Kruskal-Wallis test. Phase 2: DART scores were used to predict 1 year EF recovery after RARP. EF was defined as erections sufficient for intercourse greater than half the time, which corresponds to an answer of 4 or 5 to the third question of the International Index of Erectile Function. 12 clinical features (e.g. age, comorbidities) and 6 domains of DART scores were used to construct a machine learning model (XGBoost) to predict EF recovery. We leveraged 4-fold cross-validation to train and evaluate the model, and reported the mean and standard deviation (SD) of area under the curve (AUC) across the 4 folds on a held-out test set. RESULTS: 96 NS videos from 17 surgeons were included. The IRR among 5 assessors was moderately high (PABAK=0.62, 95% CI [0.50-0.74]), and agreement rate was 75%. Phase 1: the majority of DART sub-domains were able to distinguish the experience levels of surgeons performing the NS, and the total DART scores were significantly higher in the more experienced groups (p=0.003) (Table 1). Phase 2: AUC of the model predicting 1-year EF recovery achieved 0.72 (SD±0.16) and 0.78 (SD±0.07) using clinical features and DART scores alone, respectively. Combining both elements, AUC of the prediction model achieved 0.84 (SD±0.08). CONCLUSIONS: DART scores can distinguish surgeons with different experience levels during the NS step of RARP and can accurately predict 1-year EF recovery. Source of Funding: None © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e718 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Runzhuo Ma More articles by this author Alvin Hui More articles by this author Jiashu Xu More articles by this author Aditya Desai More articles by this author Michael Tzeng More articles by this author Emily Cheng More articles by this author Loc Trinh More articles by this author Jessica H. Nguyen More articles by this author Anima Anandkumar More articles by this author Jim C. Hu More articles by this author Andrew J. Hung More articles by this author Expand All Advertisement PDF DownloadLoading ...