Abstract
In this study, we applied graph theory to clinical decision-making for Stress Urinary Incontinence (SUI) treatment. Utilizing discrete mathematics, we developed a system to visually understand the shortest path to the desired treatment outcomes by considering various patient variables. Focusing on women aged 35-50, we examined the effectiveness of Tension-free Vaginal Tape (TVT) surgery and Vaginal Erbium Laser (VEL) treatment for over 15 years. The TVT group consisted of 102 patients who underwent surgery using either the Advantage Fit mid-urethral sling system (Boston Scientific Co., MA, USA) or the GYNECARE TVT retropubic system (Ethicon Inc., NJ, USA). The VEL group included 113 patients treated with a non-ablative Erbium: YAG laser (FotonaSmooth™ XS; Fotona d.o.o., Ljubljana, Slovenia), and there were 112 patients in the control group. We constructed a network diagram analyzing the correlations between health, demographic factors, treatment methods, and patient outcomes. By calculating the shortest path using heuristic functions, we identified significant correlations and treatment effects. This approach supports patient decision making by choosing between TVT and VEL treatments based on individual objectives. Our findings provide new insights into SUI treatment, highlighting the value of a data-driven personalized approach for clinical decision-making. This interdisciplinary study bridges the gap between mathematics and medicine, demonstrating the importance of a data-centric approach in clinical decisions.