PD01-08 PREDICTING RESIDUAL STONE FRAGMENTS IN PATIENTS UNDERGOING URETEROSCOPY IS DIFFICULT DESPITE SIGNIFICANT ASSOCIATIONS BETWEEN PREDICTORS AND OUTCOME: RESULTS FROM THE MUSIC STATEWIDE COLLABORATIVE

Abstract

You have accessJournal of UrologyStone Disease: Surgical Therapy I (PD01)1 Apr 2020PD01-08 PREDICTING RESIDUAL STONE FRAGMENTS IN PATIENTS UNDERGOING URETEROSCOPY IS DIFFICULT DESPITE SIGNIFICANT ASSOCIATIONS BETWEEN PREDICTORS AND OUTCOME: RESULTS FROM THE MUSIC STATEWIDE COLLABORATIVE Richard Wu*, Adharsh Murali, Colton Walker, Casey Dauw, Kavya Swarna, Arvin George, Khurshid Ghani, Jill Slayton, Karandeep Singh, and for the Michigan Urological Surgery Improvement Collaborative Richard Wu*Richard Wu* More articles by this author , Adharsh MuraliAdharsh Murali More articles by this author , Colton WalkerColton Walker More articles by this author , Casey DauwCasey Dauw More articles by this author , Kavya SwarnaKavya Swarna More articles by this author , Arvin GeorgeArvin George More articles by this author , Khurshid GhaniKhurshid Ghani More articles by this author , Jill SlaytonJill Slayton More articles by this author , Karandeep SinghKarandeep Singh More articles by this author , and for the Michigan Urological Surgery Improvement Collaborative More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000821.08AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Although one of the measures of successful ureteroscopy (URS) for stone disease is the absence of residual stone fragments, limited evidence is available on whether it is possible to predict which patients will have residual fragments following URS. Availability of a risk model would help identify patients who may benefit from follow-up imaging and additional procedures. We sought to determine whether residual stone fragments following URS can be predicted using data from a large prospective clinical registry. METHODS: The Michigan Urological Surgery Improvement Collaborative (MUSIC) is a consortium of 46 diverse urology practices, of which 40 have participated in a registry of patients with kidney and ureteral stones since 2016. Among patients who underwent URS with available pre and post URS imaging, we developed univariable and multivariable logistic regression models to predict stone-free status using demographic and stone-related factors, including age, sex, body mass index, presence of diabetes, size of largest stone visualized, location of stone(s), number of stones, and presence of pre-procedure hydronephrosis and urinary tract infection. We assessed model discrimination using 5 fold cross-validated area-under-the-curve (AUC). RESULTS: We identified 3,971 patients who underwent URS with available pre- and post-URS imaging, of whom 1,700 (42.8%) had residual stone fragments. Variables with statistically significant associations with residual stone fragments in both univariable and multivariable models included age, body mass index, stone size, several stone locations, and number of kidney stones (Table 1). Cross-validated AUC for the model was 0.635.Table 1. Odds ratios for univariable and multivariable analysis for predicting residual stone fragments following URS. CONCLUSIONS: Despite statistically significant associations between several predictors and the outcome, a logistic regression model predicting presence of post-URS residual stone fragments had poor discrimation. Source of Funding: Blue Cross Blue Shield of Michigan © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e62-e63 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Richard Wu* More articles by this author Adharsh Murali More articles by this author Colton Walker More articles by this author Casey Dauw More articles by this author Kavya Swarna More articles by this author Arvin George More articles by this author Khurshid Ghani More articles by this author Jill Slayton More articles by this author Karandeep Singh More articles by this author for the Michigan Urological Surgery Improvement Collaborative More articles by this author Expand All Advertisement PDF downloadLoading ...