首页|Department of Reproductive Medicine Center Reports Findings in Urinary Incontine nce (Prediction models for urinary incontinence after robotic-assisted laparosco pic radical prostatectomy: a systematic review)
Department of Reproductive Medicine Center Reports Findings in Urinary Incontine nce (Prediction models for urinary incontinence after robotic-assisted laparosco pic radical prostatectomy: a systematic review)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Urologic Diseases and Conditions-Urinary Incontinence is the subject of a report. According to news originating from Changchun, People's Republic of China, by NewsRx correspondents , research stated, "Even though robotic-assisted laparoscopic radical prostatect omy (RARP) is superior to open surgery in reducing postoperative complications, 6-20% of patients still experience urinary incontinence (UI) after surgery. Therefore, many researchers have established predictive models for UI occurrence after RARP, but the predictive performance of these models is inconsi stent." Our news journalists obtained a quote from the research from the Department of R eproductive Medicine Center, "This study aims to systematically review and criti cally evaluate the published prediction models of UI risk for patients after RAR P. We conducted a comprehensive literature search in the databases of PubMed, Co chrane Library, Web of Science, and Embase. Literature published from inception to March 20, 2024, which reported the development and/or validation of clinical prediction models for the occurrence of UI after RARP. We identified seven studi es with eight models that met our inclusion criteria. Most of the studies used l ogistic regression models to predict the occurrence of UI after RARP. The most c ommon predictors included age, body mass index, and nerve sparing procedure. The model performance ranged from poor to good, with the area under the receiver op erating characteristic curves ranging from 0.64 to 0.98 in studies. All the stud ies have a high risk of bias. Despite their potential for predicting UI after RA RP, clinical prediction models are restricted by their limited accuracy and high risk of bias. In the future, the study design should be improved, the potential predictors should be considered from larger and representative samples comprehe nsively, and high-quality risk prediction models should be established."
ChangchunPeople's Republic of ChinaA siaEmerging TechnologiesHealth and MedicineIncontinenceMachine LearningMale Urologic Surgical ProceduresMen's HealthProstatectomyRoboticsRobot sSurgeryUrinary IncontinenceUrologic Diseases and ConditionsUrology
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