You have accessJournal of UrologyGeneral & Epidemiological Trends & Socioeconomics: Practice Patterns, Quality of Life and Shared Decision Making IV1 Apr 2017MP76-07 PREDICTING COMPLICATIONS FOLLOWING ROBOT-ASSISTED PARTIAL NEPHRECTOMY WITH THE ACS-NSQIP UNIVERSAL SURGICAL RISK CALCULATOR Jared S. Winoker, Harry Anastos, David J. Paulucci, Nikhil Waingankar, John P. Sfakianos, and Ketan K. Badani Jared S. WinokerJared S. Winoker More articles by this author , Harry AnastosHarry Anastos More articles by this author , David J. PaulucciDavid J. Paulucci More articles by this author , Nikhil WaingankarNikhil Waingankar More articles by this author , John P. SfakianosJohn P. Sfakianos More articles by this author , and Ketan K. BadaniKetan K. Badani More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.2135AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Assessment of surgical risk is integral to patient counseling and shared clinical decision-making. The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) surgical risk calculator is an easily accessible, online tool for predicting surgical outcomes after a variety of procedures. Little is known of the tool's applicability to urologic surgery. We sought to evaluate the predictive value of the calculator in a tertiary referral cohort of patients undergoing robot-assisted partial nephrectomy (RAPN). METHODS We queried our prospectively maintained multi-institutional database of RAPN (n=1260) from 2008 to 2016. Preoperative details of 300 randomly selected patients were entered into the calculator. The predicted rates of complications were compared with the actual rates of observed complications. Validation of the calculator was assessed by receiver-operator area under the curve (AUC) for discrimination and Brier score (BS) for calibration. Calculated BS was also compared to a null model (null-BS); a BS lower than the null model indicates stronger predictive power for that individual outcome where a BS of zero indicates perfect prediction. RESULTS The observed rate of any complication in our cohort was 14%, comparable with that reported in the literature, while the mean predicted rate of any complication was 5.42%. The calculated AUC for any complications was 0.51. Our cohort demonstrated a serious complication (Clavien Score ≥ 3) rate of 3.67%, lower than the predicted rate of 4.89% (AUC 0.55). The majority of the captured complications had a low BS, indicative of good calibration. However, the calculated AUC was low for all outcomes, indicating poor discrimination ability. Venous thromboembolism (VTE) and readmission had the highest AUCs - 0.67 and 0.69, respectively. CONCLUSIONS The ACS-NSQIP risk calculator poorly predicted most complications after RAPN. The model had marginal accuracy for predicting VTE and readmissions, and good accuracy for predicting the rate of serious complications, but it lacked the power to discriminate which patients were at risk to have such outcomes. These findings suggest the need for a more tailored outcome prediction model to accurately assist surgeons in counseling patients undergoing RAPN. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e1015 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Jared S. Winoker More articles by this author Harry Anastos More articles by this author David J. Paulucci More articles by this author Nikhil Waingankar More articles by this author John P. Sfakianos More articles by this author Ketan K. Badani More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...