Purpose: We report the prevalence of stress urinary incontinence and pelvic organ prolapse in patients with multiple sclerosis referred to a tertiary care neurogenic bladder clinic.
Materials And Methods: We queried an institutional review board approved neurogenic bladder database for urodynamic and demographic data on patients with multiple sclerosis followed for lower urinary tract symptoms in a 12-year period. Demographic information included multiple sclerosis classification, age at initial visit, body mass index, parity and pelvic examination findings. Prolapse was defined as stage 2 prolapse or greater. Stress urinary incontinence was defined as urodynamic stress incontinence and/or incontinence on a supine stress test.
Results: Included in analysis were 280 women with a mean age of 50 years and a mean 13-year history of multiple sclerosis. Relapse remitting multiple sclerosis was noted in 40% of patients, while 45 (16%) had stress urinary incontinence. Women with stress urinary incontinence had a higher average maximum urine flow (14 vs 9 ml per second, p <0.003), higher voided volume (272 vs 194 cc, p = 0.018) and higher body mass index (30 vs 25 kg/m(2), p <0.005). Overall, 23 women (9%) had pelvic organ prolapse, including 2 (9%) with posterior prolapse only, 8 (35%) with anterior prolapse only and 13 (56%) with posterior and anterior prolapse. There was no difference in age, body mass index or multiple sclerosis subtype between women with vs without pelvic organ prolapse.
Conclusions: The 14% prevalence of demonstrable stress urinary incontinence and 9% rate of pelvic organ prolapse are markedly lower than published historical data on an age matched cohort without multiple sclerosis. The surprisingly low prevalence of stress urinary incontinence and pelvic organ prolapse in women with multiple sclerosis may be attributable to decreased activity, a neurogenically enhanced vesicourethral unit or other functional or anatomical etiologies.
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http://dx.doi.org/10.1016/j.juro.2012.09.101 | DOI Listing |
Front Immunol
January 2025
Institut National de la Santé et de la Recherche Médicale (INSERM), Unité Mixte de Recherche U1236, Université Rennes, Etablissement Français du Sang Bretagne, LabEx IGO, Rennes, France.
Introduction: Myeloid cells trafficking from the periphery to the central nervous system are key players in multiple sclerosis (MS) through antigen presentation, cytokine secretion and repair processes.
Methods: Combination of mass cytometry on blood cells from 60 MS patients at diagnosis and 29 healthy controls, along with single cell RNA sequencing on paired blood and cerebrospinal fluid (CSF) samples from 5 MS patients were used for myeloid cells detailing.
Results: Myeloid compartment study demonstrated an enrichment of a peculiar classical monocyte population in 22% of MS patients at the time of diagnosis.
Front Immunol
January 2025
Department of Neurosciences, University of Padua, Padua, Italy.
Pediatric-Onset Multiple Sclerosis (POMS) is characterized by both white and grey matter inflammation, as well as by a higher risk of long-term physical and cognitive disability. The peculiar immunopathogenic mechanisms of POMS suggests that the use of induction therapies, including alemtuzumab (ALTZ), might be a promising approach, at least for postpuberal (> 11 yo) POMS. Although no data on the use of induction therapies in POMS are available from clinical trials currently, case series or case reports on the effect of alemtuzumab (ALTZ) have been recently published.
View Article and Find Full Text PDFBrain Behav Immun Health
February 2025
Centre for Infection and Immunity Studies, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, 518107, China.
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View Article and Find Full Text PDFR Soc Open Sci
January 2025
University Hospitals Birmingham NHS Foundation Trust, Edgbaston, Birmingham B15 2GW, UK.
Multiple sclerosis (MS) is an autoimmune disease of the brain and spinal cord with both inflammatory and neurodegenerative features. Although advances in imaging techniques, particularly magnetic resonance imaging (MRI), have improved the process of diagnosis, its cause is unknown, a cure remains elusive and the evidence base to guide treatment is lacking. Computational techniques like machine learning (ML) have started to be used to understand MS.
View Article and Find Full Text PDFBMJ Med
January 2025
Laboratory Medicine - Neurochemistry, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
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