MP34-03 ASSOCIATION OF MANUAL AND AUTOMATED PERFORMANCE METRICS WITH URINARY CONTINENCE RECOVERY AFTER ROBOT-ASSISTED RADICAL PROSTATECTOMY

Abstract

You have accessJournal of UrologySurgical Technology & Simulation: Training & Skills Assessment I (MP34)1 Apr 2020MP34-03 ASSOCIATION OF MANUAL AND AUTOMATED PERFORMANCE METRICS WITH URINARY CONTINENCE RECOVERY AFTER ROBOT-ASSISTED RADICAL PROSTATECTOMY Samuel Mingo*, Runzhuo Ma, Jessica Nguyen, Erik Vanstrum, and Andrew Hung Samuel Mingo*Samuel Mingo* More articles by this author , Runzhuo MaRunzhuo Ma More articles by this author , Jessica NguyenJessica Nguyen More articles by this author , Erik VanstrumErik Vanstrum More articles by this author , and Andrew HungAndrew Hung More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000878.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Previous studies link surgeon performance during the vesicourethral anastomosis (VUA) to urinary continence recovery (CR) time after robot-assisted radical prostatectomy (RARP). Automated performance metrics (APMs) assess surgeon efficiency while manually-observed metrics (e.g. Robotic Anastomosis Competency Evaluation (RACE)) evaluate surgeon technical skills. In conjunction, these metrics create a comprehensive measure of surgeon performance. Our study determines the association between APMs and RACE as assessment tools during the VUA with CR. METHODS: Clinicopathological data was collected prospectively at USC. Surgical video and APMs (kinematic and system data) were recorded (Intuitive Surgical) and collected from a da Vinci robot. RACE was assessed by 3 individuals. Analysis 1: Spearman’s coefficient determined between RACE and APMs. Analysis 2: Univariate analysis determined how patient factors, RACE, and APMs predict CR time. Analysis 3: Multivariate analysis determined if significant parameters found in Analysis 2 independently predict CR time. CR time established as 0 to 1 safety pad after RARP. RESULTS: 103 RARPs performed by 21 surgeons were analyzed. Median CR time of 166 days (16-553 range). Median RACE of 29 (25-30). Median surgeon RARP experience of 135 cases (30–2000). Analysis 1: Spearman’s correlation coefficient of total RACE and APMs yield a weak association (-0.210<ρ<0.339 p<0.038) Analysis 2: Cox regression yielded patient age as predictive of CR (HR=0.960 p=0.011). For RACE, needle positioning (HR=2.392, p<0.001), suture placement (HR=2.505 p=0.001), and tissue approximation (HR=2.505 p<0.001) domains were predictive of CR. For APMs, moving time of dominant instrument (HR=0.999 p=0.011), dominant instrument articulation (HR=0.999 p=0.025), and linear velocity of dominant instrument (HR=1.019 p<0.001) were predictive of CR. Analysis 3: Cox regression returned patient age as predictive (HR=0.943 p=0.002). For RACE, needle positioning (HR=1.880 p=0.008), suture placement (HR=2.317 p=0.005), and tissue approximation (HR=2.163 p=0.005) domains were predictive. For APMs, wrist translation of dominant instrument (HR=0.998 p=0.018), and linear velocity of dominant instrument (HR=1.015 p=0.018) were independently predictive of CR time. CONCLUSIONS: Surgical skills, as measured by automated and manual assessments, can predict clinical outcomes. In our study, RACE evaluation of technical skills were stronger predictors of CR time than APM assessments of surgical efficiency. Source of Funding: This study was funded in part by an Intuitive Surgical Clinical Grant; Intuitive Surgical provided the systems data recorder. Research reported in this publication was supported in part by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number K23EB026493. © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e503-e504 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Samuel Mingo* More articles by this author Runzhuo Ma More articles by this author Jessica Nguyen More articles by this author Erik Vanstrum More articles by this author Andrew Hung More articles by this author Expand All Advertisement PDF downloadLoading ...