Neurourological assessment in people with multiple sclerosis (MS): a new evaluated algorithm

BACKGROUND Neurogenic lower urinary tract dysfunction (NULTD) is common in patients with multiple sclerosis (MS); nevertheless, it is often underestimated, underdiagnosed, and undertreated due to patients' sense of shame, variability of symptoms, as well as lack of communication between neurologists and urologists, despite the availability of several guidelines based on scientific evidence and expert opinion. OBJECTIVE This study was conducted to develop an easy-to-perform algorithm for diagnosing neurogenic lower urinary tract disease in patients with MS for daily neurological and urological routine, including the identification of red flags. METHODS In consensus group meetings, interprofessional experts (neurologists, urologists, neurourologists, nurses, nurse practitioners, occupational therapists, physical therapists as well as representatives of national MS centers, self-care groups, social care, residential care, and health-aid-providers) developed a diagnostic algorithm to detect NULTD in patients with MS. Subsequently, the group evaluated the algorithm in 121 patients with MS using micturition diary, post-void residual volume, uroflowmetry, and urodynamic studies. Statistical analysis was conducted on the basis of logistic regression models to compare patients with normal and abnormal urodynamic examinations. Differentiation was performed using selected diagnostic parameters as well as standard performance measures for binary classifiers to assess prognostic quality. RESULTS The following four parameters allowed to diagnose NLUTD in patients with MS: post-void residual urine volume, rate of urinary tract infections during the past 6 months, micturition frequency, and incontinence. According to statistical analysis, the following thresholds could be defined: post-void residual volume (PVR) ≥70 mL (Odds Ratio (OR) = 1.24; 95% CI:[1.07,1.62]), urinary tract infection (UTI) rate - none in 6 months (OR = 2.03; 95% CI:[1.04,6.68]), and micturition frequency >13/day, standardized on 2000 mL urine excretion (OR = 1.24; 95% CI:[1.07,1.49]). Uroflowmetry served as a further predictor of urodynamically measurable urinary bladder dysfunction (OR = 4.80; 95% CI: [1.41, 19.21]). Interestingly, patients without any complaints of NLUTD had an abnormal urodynamic examination in >50% of the cases. The entire algorithm has a sensitivity of 95%. CONCLUSIONS All patients with MS should undergo a basic examination to detect NLUTDs. Within the algorithm developed in this study, four easy-to-collect parameters may reveal NLUTD in patients with MS.