Personalized Behavioral Modifications Algorithm and Software Based on Analysis and Computer Simulation of Voiding Patterns in Patients with Lower Urinary Tract Symptoms

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7. Project Summary/Abstract Lower urinary tract symptoms (LUTS), such as urinary urgency, frequency, nocturia, and incontinence affect approximately three-quarters of the population over age 40 in the United States and are associated with decreased quality of life. Bladder Diaries are a simple, inexpensive tool to capture real-life symptoms and voiding behavior. Simple recommendations based on the Bladder Diaries have already been shown to have a profound impact on LUTS, including incontinence. We are striving to go further and develop individualized advice for patients, rather than a generic “drink less, void every 2 hours, and restrict fluids before bed” recommendation, which may not improve LUTS in all patients. Bladder Diaries provide the timing of fluid intake, which is the primary driver of urinary output, but the time lapse between intake and output is not straightforward. To fill this knowledge gap, we plan to develop a parsimonious mechanistic model based on current understanding of the physiology and neural regulation of urination and fluid shifts in the body that describes voiding patterns in people with and without LUTS. We will be using Bladder Diary data collected in two studies: Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) and Establishing Prevalence of Incontinence (EPI). The mathematical model will consider: 1) ingestion time and amount; 2) variability in delivery to the bladder; and 3) variation in bladder sensation and excretion. This model could serve future researchers in evaluation of voiding variables and in mechanistic studies of LUTS. Based on the model, we plan to develop an algorithm and software to provide individualized recommendations to modify intake patterns in order to minimize “adverse urinary events” (i.e., leaking or excessive night voids). Optimization of the intake patterns will be performed to minimize number of simulated adverse urinary events for a given simulated patient based on the model developed from the Bladder Diary of a real patient. The goal is to develop a “precision medicine” tool for assessment of Bladder Diaries so that clinicians will be able to provide individualized behavior modification recommendations. This work would represent the first systematic mathematical model of fluid intake and voiding behavior based on Bladder Diary data that would help understanding individual voiding patterns, mechanisms of disease, and opportunities for treatment.