Clinical Characteristics and Urodynamic Analysis of Urinary Dysfunction in Multiple Sclerosis

Background: Both lower urinary tract dysfunction and urinary symptoms are prevalent in patients with multiple sclerosis (MS). Although the significance of identifying and treating urinary symptoms in MS is currently well-known, there is no information about the real prevalence and therapeutic effect of urinary symptoms in patients with MS. The purpose of this study was to analyze the major symptoms and urodynamic abnormalities, and observe the therapeutic effect in different MS characteristics. Methods: We enrolled 126 patients with urological dysfunction who were recruited between July 2008 and January 2015 in Beijing Tian Tan Hospital, Capital Medical University and conducted overactive bladder system score (OABSS), urodynamic investigation, and expanded disability status scale (EDSS). Changes of urinary symptoms and urodynamic parameters were investigated. Results: Urgency was the predominant urinary symptom, and detrusor overactivity was the major bladder dysfunction. There was a positive correlation between EDSS and OABSS. Clinically isolated syndrome (CIS) had lowest EDSS and OABSS. CIS exhibited significant improvements in OABSS, maximum urinary flow rate (Qmax), and bladder volume at the first desire to voiding and maximum bladder volume after the treatment (P < 0.05). Relapsing-remitting MS showed significant improvements in the OABSS, Qmax, and bladder volume at the first desire to voiding, maximum bladder volume and bladder compliance after the treatment (P < 0.05). Progressive MS exhibited significant increase in the bladder volume at the first desire to voiding, the detrusor pressure at maximum flow rate (PdetQmax), and bladder compliance after the treatment (P < 0.05). Conclusions: Urodynamic parameters examined are important in providing an accurate diagnosis, guiding management decisions of MS. Early and effective treatment may improve the bladder function and the quality of life at the early stages of MS.

Abstract licence: CC BY-NC-ND

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.