Assessment of Renal Deterioration and Associated Risk Factors in Patients With Multiple Sclerosis

[Current aspects of neurogenic dysfunctions of the lower urinary tract in multiple sclerosis]

BACKGROUND

In the clinical management of patients with multiple sclerosis (MS), the challenge is to make an early diagnosis and initiate adequate treatment of neurogenic disorders of the lower urinary tract (NLUTD). Various national guidelines provide practical recommendations which are sometimes discordant.

OBJECTIVE

To develop a simple evidence-based algorithm for detecting NLUTD in patients with MS that could be taken as a principle for deriving therapeutic consequences.

MATERIAL AND METHODS

A prospective multicenter study was initiated as a direct result of two multidisciplinary conferences. The aim was to identify statistically and clinically relevant parameters for the routine diagnosis of NLUTD in patients with MS. Urodynamic abnormalities served as the gold standard. At three subsequent consensus conferences, the results of the study were discussed, a diagnostic algorithm was developed and consensus was reached on a first-line treatment.

RESULTS AND DISCUSSION

The proposed algorithm enables the detection of NLUTD in patients with MS with the help of four statistically significant predictors: 1) the residual urine volume, 2) the number of urinary tract infections (UTI) within the last 6 months, 3) the standardized micturition frequency and 4) the presence/absence of urinary incontinence. The newly developed algorithm has proved to be efficient with the following results: approximately 75% of the patients do not need a urodynamic examination for a first-line treatment decision. In 25% of cases, urodynamic examinations are essential for an adequate treatment decision. Routine assessments include the patient medical history, residual urine volume measurement, a micturition diary and a uroflowmetry (optional).

Are falls in people with multiple sclerosis related to the severity of urinary disorders?

BACKGROUND

Lower urinary tract symptoms (LUTSs), especially overactive bladder, are frequent in people with multiple sclerosis (PwMS). Urinary urgency and urge urinary incontinence could lead to precipitation and thus could increase the risk of falling in these individuals.

OBJECTIVE

We aimed to assess the association between severity of LUTSs and risk of falling in PwMS.

METHODS

PwMS with LUTSs were recruited in a neuro-urology department. Participants were asked about the number of falls in the past 3 months and their circumstances. Severity of LUTSs was assessed by the Urinary Symptoms Profile (USP) score, and individuals were classified as with or without urinary incontinence.

RESULTS

This cross-sectional study included 154 patients (69% women); the mean (SD) age was 50.1 (11.5) years and median EDSS was 5 (interquartile range 3-6). Overall, 20 (13%) patients reported one fall during the past 3 months, and 43 (28%) reported at least 2 falls. Only 9 (6%) patients reported a fall on the way to the toilet, 6 during a urinary urgency. No link was found between falls and urinary incontinence (P=0.71), type or severity of urinary symptoms (overactivity, voiding dysfunction or stress incontinence, P>0.05). Falls on the way to the bathroom was associated with high USP score related to overactive bladder (P=0.03) and severe nocturia (>2 nocturnal micturitions) (P<0.01). Falling at night was also associated with severe nocturia (P<0.001).

CONCLUSIONS

The severity of LUTSs and presence of urinary incontinence do not appear related to the risk of falling in PwMS and urinary disorders but rather to the specific risk of falling on the way to the bathroom. Severe nocturia increases the risk of falling at night. Further studies are needed to assess the impact of LUTS treatment on the risk of falling. ClinicalTrials.gov (NCT04338646).

Create a predictive model for neurogenic bladder patients: upper urinary tract damage predictive nomogram

Objective: To create a nomogram to evaluate the risk of upper urinary tract damage (UUTD) in patients with neurogenic bladder (NGB) Methods: A retrospective analysis was conducted on 301 patients with NGB who were admitted to certain hospitals. Data collected included clinical symptoms, patients' characteristics, laboratory parameters, imaging findings, and urodynamic parameters. The least absolute shrinkage and selection operator（LASSO）regression model was used to optimise the selection of predictors. Multivariate logistic regression analysis was performed to develop a UUTD risk predictive model. Validation was performed by bootstrap. Results: The predictors included in the nomogram included sex, duration of disease, history of UTI, bladder compliance, and fecal incontinence. The model presented good discrimination with a C-index value of 0.796 (95% confidence interval: 0.74896-0.84304) and good calibration. The C-index value of the interval validation was 0.7872112. The results of decision curve analysis (DCA) demonstrated that the UUTD-risk predictive nomogram was clinically useful. Conclusion: The nomogram incorporating the sex, duration of disease, history of UTI, bladder compliance, and fecal incontinence could be an important tool of UUTD risk prediction in NGB patients.