Development and Validation of Urodynamic Report Writer: A Chat GPT App.

OBJECTIVE: Accurate interpretation and reporting of urodynamic studies are essential for diagnosis and management of lower urinary tract dysfunction, yet remain time-consuming and operator-dependent. To develop and validate the Urodynamic Report Writer App (URapp), a GPT-4o-based virtual assistant that supports interpretation of clinician-supplied urodynamic data and draft report generation. METHODS: Multiphase development and validation study. URapp was modeled using scientific literature and international urodynamic guidelines. Training used urodynamic examinations from multiple referral centers, with supervised fine-tuning by two expert urodynamicists. Validation was performed by functional urology specialists using a Likert scale (0-5) assessing clinical relevance, interpretative accuracy, diagnostic usefulness, clarity of urodynamic concept explanations, practical recommendations, and adherence to evidence-based standards. In the final phase, URapp generated reports for a consecutive sample of 100 urodynamic studies, independently evaluated by two expert urologists. RESULTS: Development required approximately 6 months. Validation scores were high across domains: interpretative accuracy (4.5 ± 0.2), explanation of urodynamic concepts (5.0 ± 0), adherence to evidence-based standards (4.8 ± 0.3), clarity and practicality of recommendations (4.2 ± 0.3), clinical relevance (3.8 ± 0.3), and diagnostic usefulness (3.5 ± 0.5). All 100 consecutive cases (median age 61 yr) received overall scores ≥4. Limitations include retrospective design, limited sample size, and absence of prospective clinical outcome assessment. CONCLUSIONS: URapp may support standardized, guideline-adherent urodynamic reporting in clinical practice. Prospective multicenter studies are required before routine clinical implementation.