Abdominal wall reconstruction with transversus abdominus release (TAR) requires space of Retzius dissection for retropubic mesh placement. Retzius space dissection has been associated with postoperative urinary incontinence (UI) in urologic literature, but implications of retropubic dissection are unreported for patients undergoing retromuscular ventral hernia repair. This quality assurance (QA) initiative sought to characterize pre- and postoperative UI prevalence at a high-volume hernia practice to inform risk–benefit discussions and surgical decision-making. Patients offered TAR, or who had previously undergone TAR, were given a Urinary Distress Inventory Short-Form (UDI-6) survey as a part of clinical workflow. UI was defined by UDI-6 score ≥33.33, consistent with prior literature. A deidentified QA database captured responses and respondents’ age and gender. UI prevalence, UDI-6 total score, and patient characteristics were compared across preoperative, early postoperative, 1-year, and ≥ 2-year cohorts. A matched analysis was conducted for preoperative surveys that could be paired with a postoperative survey from the same patient. The study is reported according to the SQUIRE 2.0 guidelines. Of 304 UDI-6 surveys, 82 (26.9

Bladder spasms and irritative lower urinary tract symptoms (LUTS) are a common complication following urologic procedures, causing significant discomfort and potentially compromising therapeutic outcomes. Intravesical therapy, which enables localized drug delivery and limits systemic toxicity, relies on the urinary bladder as a reservoir accessible via urethral catheterization. However, direct mucosal exposure to chemotherapeutic and immunotherapeutic agents frequently provokes irritative LUTS, ranging from dysuria and discomfort to bladder spasms. In patients receiving intravesical therapy for non-muscle-invasive bladder cancer (NMIBC), spasms may lead to premature drug expulsion, severe cystitis symptoms or discontinuation of therapy. This concern is of particular relevance given the recent approval of several novel intravesical agents for the treatment of Bacillus Calmette-Guérin (BCG)-unresponsive NMIBC, including nadofaragene firadenovec and nogapendekin alfa inbakicept. While evidence for managing adverse urinary symptoms with these newer agents remains limited, various management strategies, such as anticholinergics, β3-adrenergic agonists, and adjunctive therapies, have been explored for similar presentations. In this review, we evaluate the etiology of bladder spasms and irritative LUTS associated with currently approved intravesical therapies for bladder cancer and current approaches to preventing and managing them. By synthesizing available evidence and clinical practice insights, we aim to provide practical recommendations to optimize intravesical therapy for bladder cancer outcomes.

Uterosacral ligament vaginal vault suspension (USVVS) is commonly performed for pelvic organ prolapse and offers a minimally invasive alternative to the transabdominal route. Nonetheless, as with any major surgical procedure, there are complications specific to this approach. Complications common to many reconstructive procedures, including urinary tract infection, wound infection, venous thrombosis, and positioning-related neuropraxias, are discussed elsewhere. We focus on the most common complications specific to USVVS including hemorrhage, ureteral injury, bowel injury or obstruction, and peripheral nerve injury.

You have accessJournal of UrologyUrodynamics/Lower Urinary Tract Dysfunction/Female Pelvic Medicine: Overactive Bladder I (PD43)1 May 2024PD43-07 SACRAL NEUROMODULATION DEVICE BIOFILMS DIFFER IN COMPOSITION BY INFECTION STATUS AND TESTING PHASE Glenn Werneburg, Daniel Hettel, Sandip Vasavada, Howard Goldman, Ava Adler, Bradley Gill, Raymond Rackley, Jacqueline Zillioux, Sarah Martin, Sromona Mukherjee, Daniel Shoskes, and Aaron Miller Glenn WerneburgGlenn Werneburg , Daniel HettelDaniel Hettel , Sandip VasavadaSandip Vasavada , Howard GoldmanHoward Goldman , Ava AdlerAva Adler , Bradley GillBradley Gill , Raymond RackleyRaymond Rackley , Jacqueline ZilliouxJacqueline Zillioux , Sarah MartinSarah Martin , Sromona MukherjeeSromona Mukherjee , Daniel ShoskesDaniel Shoskes , and Aaron MillerAaron Miller View All Author Informationhttps://doi.org/10.1097/01.JU.0001009568.19060.25.07AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Sacral neuromodulation (SNM) is effective for urinary retention and medically-refractory overactive bladder. A subset of implanted SNM devices is associated with infection requiring surgical removal. We aimed to compare microbial compositions of SNM device biofilms in the presence and absence of infection and other clinical factors. We hypothesized that SNM devices would have significantly different biofilm composition by infection status and testing phase prior to initial device placement. METHODS: Urological patients scheduled to undergo removal of SNM devices were consented per IRB-approved protocol. Devices were swabbed intraoperatively upon exposure during explantation. Samples and controls were analyzed using next-generation sequencing. Associations between microbial diversity and microbial abundance, and clinical variables were then analyzed using t-tests and ANOVA. RESULTS: 37 devices were analyzed. Biofilms were consistently detected even in the absence of infection, and microbial beta diversity differed in the presence versus absence of infection (p=0.01, Figure panel A). Proteobacteria, Firmicutes, and Actinobacteriota were the most common phyla present. There were lower microbial counts in biofilms from sacral neuromodulation devices that were implanted following percutaneous nerve evaluation (PNE) versus a stage 1 testing phase (p<0.001, Figure panel B). CONCLUSIONS: SNM device biofilms harbored unique microbiota in the presence and absence of infection. There were lower microbial counts detected in device biofilms from devices that were initially implanted following a PNE versus a stage 1 testing phase. The findings open new avenues for investigation of the pathophysiological transition of a medical device from a colonized asymptomatic state to an infected state, and identify preventative strategies. Download PPT Source of Funding: SUFU Foundation Neuromodulation Award © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e901 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Glenn Werneburg More articles by this author Daniel Hettel More articles by this author Sandip Vasavada More articles by this author Howard Goldman More articles by this author Ava Adler More articles by this author Bradley Gill More articles by this author Raymond Rackley More articles by this author Jacqueline Zillioux More articles by this author Sarah Martin More articles by this author Sromona Mukherjee More articles by this author Daniel Shoskes More articles by this author Aaron Miller More articles by this author Expand All Advertisement PDF downloadLoading ...

A 44-year-old female with history of a transobturator tape sling presented at her four week visit with post-operative complications of urinary retention, urinary urgency and frequency, and a urethral stricture on exam. A diagnostic cystoscopy was performed that was unremarkable other than a urethral stricture. Urethral stricture was managed by urethral dilation in the office. Over the next year, symptoms worsened, and new onset vaginal pain occurred. She was seen by a different gynecologist and cystoscopy was repeated.

Introduction:Intradetrusor onabotulinumtoxinA (Botox) injections, to treat idiopathic overactive bladder (OAB), can be performed in the office setting under local analgesia alone or in the operating room (OR) under local and/or sedation. The objective of this study was to compare the symptomatic improvement in patients with OAB who underwent treatment with intradetrusor onabotulinumtoxinA injections in an in-office versus the OR setting. Methods:We performed a multicenter retrospective cohort study of women with the diagnosis of refractory non-neurogenic OAB who elected to undergo treatment with intradetrusor onabotulinumtoxinA injections between January 2015 and December 2020. The electronic medical records were queried for all the demographic and peri-procedural data, including the report of subjective improvement post procedure. Patients were categorized as either "in-office" versus "OR" based on the setting in which they underwent their procedure. Results:Five hundred and thirty-nine patients met the inclusion criteria: 297 (55%) in the in-office group and 242 (45%) in the OR group. A total of 30 (5.6%) patients reported retention after their procedure and it was more common in the in-office group (8.1%) versus the OR group (2.5%), (P = 0.003). The rate of urinary tract infection within 6 months of the procedure was higher in the OR group (26.0% vs. 16.8%, P = 0.009). The overall subjective improvement rate was 77% (95% confidence interval: 73%-80%). Patients in the OR group had a higher reported improvement as compared to the in-office group (81.4% vs. 73.3%, P = 0.03). Conclusions:In this cohort study of patients with OAB undergoing intradetrusor onabotulinumtoxinA injections, post procedural subjective improvement was high regardless of the setting in which the procedure was performed.

INTRODUCTION/PURPOSE:Sacral neuromodulation (SNM) is effective therapy for overactive bladder refractory to oral therapies, and non-obstructive urinary retention. A subset of SNM devices is associated with infection requiring surgical removal. We sought to compare microbial compositions of explanted devices in the presence and absence of infection, by testing phase, and other clinical factors, and to investigate antibiotic resistance genes present in the biofilms. We analyzed resistance genes to antibiotics used in commercially-available anti-infective device coating/pouch formulations. We further sought to assess biofilm reconstitution by material type and microbial strain in vitro using a continuous-flow stir tank bioreactor, which mimics human tissue with an indwelling device. We hypothesized that SNM device biofilms would differ in composition by infection status, and genes encoding resistance to rifampin and minocycline would be frequently detected. MATERIALS/METHODS:Patients scheduled to undergo removal or revision of SNM devices were consented per IRB-approved protocol (IRB 20-415). Devices were swabbed intraoperatively upon exposure, with controls and precautions to reduce contamination of the surrounding field. Samples and controls were analyzed with next-generation sequencing and RT-PCR, metabolomics, and culture-based approaches. Associations between microbial diversity or microbial abundance, and clinical variables were then analyzed using t-tests and ANOVA. Reconstituted biofilm deposition in vitro using the bioreactor was compared by microbial strain and material type using plate-based assays and scanning electron microscopy. RESULTS:Thirty seven devices were analyzed, all of which harbored detectable microbiota. Proteobacteria, Firmicutes and Actinobacteriota were the most common phyla present overall. Beta-diversity differed in the presence versus absence of infection (p = 0.014). Total abundance, based on normalized microbial counts, differed by testing phase (p < 0.001), indication for placement (p = 0.02), diabetes mellitus (p < 0.001), cardiac disease (p = 0.008) and history of UTI (p = 0.008). Significant microbe-metabolite interaction networks were identified overall and in the absence of infection. 24% of biofilms harbored the tetA tetracycline/minocycline resistance gene and 53% harbored the rpoB rifampin resistance gene. Biofilm was reconstituted across tested strains and material types. Ceramic and titanium did not differ in biofilm deposition for any tested strain. CONCLUSIONS:All analyzed SNM devices harbored microbiota. Device biofilm composition differed in the presence and absence of infection and by testing phase. Antibiotic resistance genes including to rifampin and tetracycline/minocycline, which are used in commercially-available anti-infective pouches, were frequently detected. Isolated organisms from SNM devices demonstrated the ability to reconstitute biofilm formation in vitro. Biofilm deposition was similar between ceramic and titanium, materials used in commercially-available SNM device casings. The findings and techniques used in this study together provide the basis for the investigation of the next generation of device materials and coatings, which may employ novel alternatives to traditional antibiotics. Such alternatives might include bacterial competition, quorum-sensing modulation, or antiseptic application, which could reduce infection risk without significantly selecting for antibiotic resistance.

OBJECTIVE To predict treatment response for overactive bladder (OAB) for a specific patient remains elusive. We sought to develop accurate models using machine learning for prediction of objective and patient-reported treatment response to intravesical botulinum toxin (OBTX-A) injection. We sought to validate the models in a challenging setting using an external dataset of a markedly different patient cohort and dosing regimen. We hypothesized the model would outperform human experts and top available algorithms. METHODS Algorithms using "operator splitting" designed for accuracy and efficiency even in small training datasets with variable completeness, were trained to predict objective response and patient-reported symptomatic improvement using the ROSETTA trial cohort and validated using the ABC trial cohort of patients who underwent OBTX-A. Areas under the curve (AUC) of algorithms were compared to the top publicly-available machine-learning classifier XGBoost, logistic regression with cross validation, and human expert predictions in the external validation set. RESULTS In the validation set, the operator splitting neural network had AUC of 0.66 and outperformed XGBoost with DART (top available machine-learning classifier, AUC: 0.58), logistic regression (AUC 0.55), and human experts (AUC 0.47-0.53) for prediction of clinical responder status. It was similarly accurate in prediction of patient subjective improvement in symptoms following OBTX-A (AUC: 0.64), again outperforming other algorithms and human experts (AUC CONCLUSION The neural network outperformed human experts and other machine-learning approaches in prediction of objective and patient-reported OBTX-A outcomes for OAB in a challenging independent validation cohort. Clinical implementation could improve counseling and treatment selection. UROLOGY 194: 56-63, 2024. (c) 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/

You have accessJournal of UrologyInfections/Inflammation/Cystic Disease of the Genitourinary Tract: Kidney & Bladder I (MP69)1 May 2024MP69-04 MACHINE LEARNING MODELS EMPLOYED AT THE TIME OF URINE SPECIMEN COLLECTION PREDICT ANTIBIOTIC RESISTANCE ON FINAL CULTURE Glenn Werneburg, Jacob Knorr, Sean McSweeney, Alex Milinovich, Lyla Mourany, Daniel Rhoads, and Sandip Vasavada Glenn WerneburgGlenn Werneburg , Jacob KnorrJacob Knorr , Sean McSweeneySean McSweeney , Alex MilinovichAlex Milinovich , Lyla MouranyLyla Mourany , Daniel RhoadsDaniel Rhoads , and Sandip VasavadaSandip Vasavada View All Author Informationhttps://doi.org/10.1097/01.JU.0001008892.86171.de.04AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Antibiotic resistance is increasing rapidly. Urine culture is the gold standard laboratory assay for urinary tract infection diagnosis, but requires up to 72 hours to result. During the time period from culture collection to final result, empiric antibiotics are frequently initiated when there is clinical suspicion for urinary tract infection (UTI). Up to 30% of empiric antibiotic prescriptions require modification upon culture finalization based on inadequate coverage. Using machine learning, we aimed to develop interpretable algorithms based on patient factors to accurately predict antibiotic resistance at the time of culture collection, three days before the final culture sensitivities resulted at our institution. We hypothesized that algorithms would accurately predict sensitivity to antibiotics. METHODS: We identified urine cultures with available sensitivities from the electronic medical record over a 7 year period. Patient factors known or suspected to be associated with antibiotic resistance were collected from the EMR and used for model training. A series of machine learning algorithms was trained to predict antibiotic resistance. Areas under the receiver operating characteristic curve (AUC) and other model performance metrics were calculated based on bootstrapping. RESULTS: 177,773 cultures from 111,938 patients were identified and used for algorithm training and validation. Top-performing models were ensemble algorithms, and predicted trimethoprim-sulfamethoxazole (TMP-SMX) resistance with AUC 0.73 (Figure 1), and nitrofurantoin resistance with AUC 0.71. The most pertinent variables within each model were identified using a drop-out method. CONCLUSIONS: Machine learning models accurately predicted microbial resistance to first line antibiotics for urinary tract infection, approximately 72 hours prior to cultures resulting. Additional validation in outside institution datasets is warranted and ongoing. Results of the present study have important implications for reduction selection pressure for antibiotic resistance through more accurately targeted therapy. Upon validation, clinical implementation of the algorithms could reduce time to resolution of symptoms and healthcare expenditures. Download PPT Source of Funding: N/A © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e1119 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Glenn Werneburg More articles by this author Jacob Knorr More articles by this author Sean McSweeney More articles by this author Alex Milinovich More articles by this author Lyla Mourany More articles by this author Daniel Rhoads More articles by this author Sandip Vasavada More articles by this author Expand All Advertisement PDF downloadLoading ...

You have accessJournal of UrologyUrodynamics/Lower Urinary Tract Dysfunction/Female Pelvic Medicine: Female Incontinence (MP23)1 May 2024MP23-18 ALGORITHMS USING OPERATOR SPLITTING AND MACHINE LEARNING OUTPERFORM HUMANS IN PREDICTION OF PATIENT-REPORTED OUTCOMES TO BOTULINUM TOXIN FOR OVERACTIVE BLADDER IN AN EXTERNAL COHORT Glenn Werneburg, Eric Werneburg, Howard Goldman, Emily Slopnick, Ly Hoang Roberts, and Sandip Vasavada Glenn WerneburgGlenn Werneburg , Eric WerneburgEric Werneburg , Howard GoldmanHoward Goldman , Emily SlopnickEmily Slopnick , Ly Hoang RobertsLy Hoang Roberts , and Sandip VasavadaSandip Vasavada View All Author Informationhttps://doi.org/10.1097/01.JU.0001008776.99097.8a.18AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: A patient's perception of symptomatic changes following an overactive bladder (OAB) therapy is a challenging prediction problem, but its solution may lead to precision optimization of OAB management. We sought to develop an accurate model using machine learning for prediction of patient-reported treatment response to intravesical botulinum toxin injection. We hypothesized the algorithm would perform superiorly to other top algorithms and expert clinicians. METHODS: Algorithms using the mathematical principle "operator splitting" were developed to predict subjective (PGI-I score) response to botulinum toxin. Algorithms were trained using the ROSETTA trial cohort data and tested and validated using the ABC trial cohort. Algorithms were designed for accuracy, efficiency, transparency, and handling of missing data and small training data sets. The ROSETTA (training set) and ABC (validation set) trials differed in inclusion criteria, data completion rates, botulinum toxin doses, and accrual time period, and thus presented a challenging predictive scenario by design. Metrics including areas under the curve (AUC) of the novel algorithms were compared to the top publicly-available machine learning classifier XGBoost, logistic regression, and human experts in the out-of-sample test set from the ABC trial. RESULTS: 167 patients from ROSETTA were included for training, and 72 from ABC for out-of-sample validation. The operator splitting neural network had AUC 0.64 and outperformed XGBoost with DART (top publicly available machine learning classifier, AUC 0.62), and human experts (AUC 0.41 – 0.54) for prediction of patient-reported subjective response to treatment in the validation set (Figure 1). CONCLUSIONS: A new machine learning model outperformed other machine learning approaches and human experts in prediction of a patients' perception of overactive bladder symptomatic improvement following botulinum toxin in an independent validation cohort. Download PPT Source of Funding: Original trials were funded by NICHD and ORWH. Data were obtained from NICHD DASH repository. The authors thanks Dr. Anthony Visco and Dr. Cindy Amundsen, principal investigators for the trials © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e389 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Glenn Werneburg More articles by this author Eric Werneburg More articles by this author Howard Goldman More articles by this author Emily Slopnick More articles by this author Ly Hoang Roberts More articles by this author Sandip Vasavada More articles by this author Expand All Advertisement PDF downloadLoading ...

OBJECTIVES:To determine accuracy of negative urinalysis (UA) for predicting negative urine culture and the absence of urinary tract infection (UTI), and optimal urine culture growth cutoff for UTI diagnosis in men with and without urinary catheters. SUBJECTS AND METHODS:UAs with urine cultures within 1 week from adult men were identified and evaluated. Predictive values for the absence of UTI (absence of ≥1 of the following criteria: documentation of UTI diagnosis, antibiotic prescription, uropathogen presence on culture) were calculated. RESULTS:In total, 22 883 UAs were included. Negative UA had a high predictive value for negative urine culture (0.95, 95% confidence interval [CI]: 0.94-0.95) and absence of UTI (0.99, CI: 0.99-0.995) in the overall cohort. Negative UA also had a high predictive value for negative urine culture (0.93, CI: 0.90-0.95) and absence of UTI (0.99, CI: 0.98-0.999) in those with indwelling urinary catheters. The traditional threshold of culture growth of 100 000 colony-forming units (CFU)/mL did not capture 22% of UTIs. CONCLUSION:UA exhibits high predictive value for negative urine culture and absence of UTI in men, supporting a protocol wherein culture is only performed in the context of abnormal UA. The traditional 100 000 CFU/mL cut-off may have not captured a subset of UTI in the male population, and warrants further investigation.