Clinical, Functional, and Therapeutic Characterization of Women With Urinary Incontinence and Analysis of Factors Associated With Treatment Response

The goal of this observational retrospective study is to characterize women with urinary incontinence and to identify factors associated with their response to treatment using artificial intelligence models. The main questions it aims to answer are: What are the clinical, functional, and therapeutic characteristics of women with urinary incontinence? Which clinical, functional, and lifestyle factors are associated with response to treatment? Can artificial intelligence models identify patterns and factors associated with treatment response? Researchers will analyze data from women with urinary incontinence collected during routine clinical care at a specialized pelvic floor clinic. The study will combine clinical information from medical records, measurements obtained from clinical assessment instruments, and daily-life data collected using wearable devices such as activity bracelets. Artificial intelligence and machine learning models will be applied to these data to characterize participants and identify factors associated with treatment response.