A model for predicting the risk of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery.
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To construct and validate a prediction model for estimating the risk of de novo stress urinary incontinence (SUI) after vaginal pelvic organ prolapse (POP) surgery and compare it with predictions using preoperative urinary stress testing and expert surgeons' predictions.Using the data set (n=457) from the Outcomes Following Vaginal Prolapse Repair and Midurethral Sling trial, a model using 12 clinical preoperative predictors of de novo SUI was constructed. De novo SUI was determined by Pelvic Floor Distress Inventory responses through 12 months postoperatively. After fitting the multivariable logistic regression model using the best predictors, the model was internally validated with 1,000 bootstrap samples to obtain bias-corrected accuracy using a concordance index. The model's predictions were also externally validated by comparing findings against actual outcomes using Colpopexy and Urinary Reduction Efforts trial patients (n=316). The final model's performance was compared with experts using a test data set of 32 randomly chosen Outcomes Following Vaginal Prolapse Repair and Midurethral Sling trial patients through comparison of the model's area under the curve against: 1) 22 experts' predictions; and 2) preoperative prolapse reduction stress testing.A model containing seven predictors discriminated between de novo SUI status (concordance index 0.73, 95% confidence interval [CI] 0.65-0.80) in Outcomes Following Vaginal Prolapse Repair and Midurethral Sling participants and outperformed expert clinicians (area under the curve 0.72 compared with 0.62, P<.001) and preoperative urinary stress testing (area under the curve 0.72 compared with 0.54, P<.001). The concordance index for Colpopexy and Urinary Reduction Efforts trial participants was 0.62 (95% CI 0.56-0.69).This individualized prediction model for de novo SUI after vaginal POP surgery is valid and outperforms preoperative stress testing, prediction by experts, and preoperative reduction cough stress testing. An online calculator is provided for clinical use.III.
Published Version (Please cite this version)
Jelovsek, J Eric, Kevin Chagin, Linda Brubaker, Rebecca G Rogers, Holly E Richter, Lily Arya, Matthew D Barber, Jonathan P Shepherd, et al. (2014). A model for predicting the risk of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery. Obstetrics and gynecology, 123(2 Pt 1). pp. 279–287. 10.1097/AOG.0000000000000094 Retrieved from https://hdl.handle.net/10161/19761.
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Dr. Jelovsek is the F. Bayard Carter Distinguished Professor of OBGYN at Duke University and serves as Director of Data Science for Women’s Health. He is Board Certified in OBGYN by the American Board of OBGYN and in Female Pelvic Medicine & Reconstructive Surgery by the American Board of OBGYN and American Board of Urology. He has an active surgical practice in urogynecology based out of Duke Raleigh. He has expertise as a clinician-scientist in developing and evaluating clinical prediction models using traditional biostatistics and machine learning approaches. These “individualized” patient-centered prediction tools aim to improve decision-making regarding the prevention of lower urinary tract symptoms (LUTS) and other pelvic floor disorders after childbirth (PMID:29056536), de novo stress urinary incontinence and other patient-perceived outcomes after pelvic organ prolapse surgery, risk of transfusion during gynecologic surgery, and urinary outcomes after mid-urethral sling surgery (PMID: 26942362). He also has significant expertise in leading trans-disciplinary teams through NIH-funded multi-center research networks and international settings. As alternate-PI for the Cleveland Clinic site in the NICHD Pelvic Floor Disorders Network, he was principal investigator on the CAPABLe trial (PMID: 31320277), one of the largest multi-center trials for fecal incontinence studying anal exercises with biofeedback and loperamide for the treatment of fecal incontinence. He was the principal investigator of the E-OPTIMAL study (PMID: 29677302), describing the long-term follow up sacrospinous ligament fixation compared to uterosacral ligament suspension for apical vaginal prolapse. He was also primary author on research establishing the minimum important clinical difference for commonly used measures of fecal incontinence. Currently, he serves as co-PI in the NIDDK Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) (U01DK097780-05) where he has been involved in studies in the development of Symptoms of Lower Urinary Tract Dysfunction Research Network Symptom Index-29 (LURN SI-29) and LURN SI-10 questionnaires for men and women with LUTS. He is also the site-PI for the PREMIER trial (1R01HD105892): Patient-Centered Outcomes of Sacrocolpopexy versus Uterosacral Ligament Suspension for the Treatment of Uterovaginal Prolapse.
Research on pelvic floor disorders. Specific interests include: 1) studying the urinary microbiome in aging, recurrent urinary tract infections, and overactive bladder; 2) pathophysiology of overactive bladder with particular emphasis on translational biology.
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