You have accessJournal of UrologyCME1 Apr 2023MP18-18 WHAT IF THEY CONTINUED THE PREGNANCY? USING PRENATAL ULTRASOUND FINDINGS TO PREDICT POSTNATAL OUTCOMES FOR FETUSES WITH LOWER URINARY TRACT OBSTRUCTION (LUTO) TO IMPROVE COUNSELING AND AID IN DECISION MAKING Juliane Richter, Shiri Shinar, Lauren Erdman, Hayley Good, Jin K. Kim, Joana Dos Santos, Natasha Brownrigg, Adree Khondker, Priyank Yadav, Michael Chua, Tim van Mieghem, Mandy Rickard, and Armando J. Lorenzo Juliane RichterJuliane Richter More articles by this author , Shiri ShinarShiri Shinar More articles by this author , Lauren ErdmanLauren Erdman More articles by this author , Hayley GoodHayley Good More articles by this author , Jin K. KimJin K. Kim More articles by this author , Joana Dos SantosJoana Dos Santos More articles by this author , Natasha BrownriggNatasha Brownrigg More articles by this author , Adree KhondkerAdree Khondker More articles by this author , Priyank YadavPriyank Yadav More articles by this author , Michael ChuaMichael Chua More articles by this author , Tim van MieghemTim van Mieghem More articles by this author , Mandy RickardMandy Rickard More articles by this author , and Armando J. LorenzoArmando J. Lorenzo More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003238.18AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: LUTO is a chronic condition with a spectrum of outcomes. It is usually suspected prenatally based on ultrasound features (USF). Given the unknown postnatal trajectory and the potential for significant morbidity and mortality, many families choose termination of pregnancy (TOP), often based on USF alone. We sought to develop a tool that can be used to predict postnatal outcomes based on combinations of USF to aid with prenatal counselling and parental decision making. METHODS: We reviewed a LUTO database from a high-risk fetal center and tertiary pediatric center and collected USF and postnatal need for urinary diversion and renal replacement therapy (RRT). USFs from a gestational age (GA) of 13-26 weeks for TOPs were collected and matched to fetuses who were not terminated to build a random forest model. Each predictor was assessed independently with combined importance when accounting for other predictors (see Table 1). The model was used to predict the most likely postnatal outcomes for TOPs had the pregnancy been continued. RESULTS: USF from 37 TOPs and 30 livebirths with postnatally confirmed LUTO were included with a follow up time of 1599 days. There were 4 postnatal deaths. Dialysis was predicted with the highest accuracy of 81% (63% sensitivity, 89% specificity), with transplant second highest (69%, 43% sensitivity, 79% specificity), and diversion the least well predicted (50% accuracy). For TOPs, had the pregnancies continued, the model predicted dialysis in 16/37 (43%), transplant in 7/37 (19%) cases, and urinary diversion in 17/37 (46%). All TOPs predicted to receive transplant were predicted to receive diversion and/or dialysis, with the majority receiving both (5/7). This is similar to the postnatal LUTO cases in which 6/7 transplanted cases received both diversion and dialysis. CONCLUSIONS: Our data suggests that it is possible to predict postnatal renal replacement therapy from USFs in TOPs had the pregnancy been continued. Predictive accuracy will improve with continued follow-up of more patients, enabling more personalized prenatal counseling and allowing for more informed decision making for families. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e230 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Juliane Richter More articles by this author Shiri Shinar More articles by this author Lauren Erdman More articles by this author Hayley Good More articles by this author Jin K. Kim More articles by this author Joana Dos Santos More articles by this author Natasha Brownrigg More articles by this author Adree Khondker More articles by this author Priyank Yadav More articles by this author Michael Chua More articles by this author Tim van Mieghem More articles by this author Mandy Rickard More articles by this author Armando J. Lorenzo More articles by this author Expand All Advertisement PDF downloadLoading ...