Multiple Sclerosis, Relapsing-Remitting Clinical Trial
Official title:
Factors Affecting Time Elapsed From First Symptom Till Complete Diagnosis of Multiple Sclerosis, Initiation of Disease Modifying Treatment and Drug Adherence in Upper Egypt
The earlier that MS can be diagnosed; the sooner treatment can be initiated with timely reduction of subclinical disease activity and prevention of disability progression. However, significant delays can still occur between noticing the first symptoms and receiving a diagnosis even before a person with symptoms suggestive of MS sees a neurologist. Such delays could be due to heterogeneity of clinical and imaging manifestations, which not only differ between patients, but also vary in individual patients over time. Moreover, lack of awareness of the primary care physicians about MS presentations, the limited accessibility to specialized centers or the non-availability of diagnostic tools such as MRI scanners and lumbar puncture, may further add to this delay and increases the risk of disability. There are also many factors that can contribute to delayed initiation of DMT after diagnosis like inadequate knowledge with DMT, their high coast and limited access to health care insurance services. Like many chronic conditions, non- Adherence to drug therapies is estimated up to 50%, with associated increased morbidity, mortality, and health care costs. To the best of our knowledge, this is the first study in upper Egypt that tries to address these factors. By conducting this study, we aim at identifying factors leading to delayed diagnosis of MS, initiation and adherence to DMT in order to translate recent advances in the diagnosis and treatment of MS into improved outcomes in the lives of people with MS and their families and to avoid many of the long-term economic and personal costs that result from unnecessary irreversible disability.
this is cross-sectional study in the Neuropsychiatry department, South Valley university hospitals, where patients with remitting relapsing multiple sclerosis according to McDonald criteria 2017 using disease modifying treatment for at least 3 months are recruited. patients were recruited from 3 major MS clinics in Assiut, South valley and Luxor. each patient was subjected to the following: - Full history and neurological examination including EDSS scores. - MRI brain and spine. - Electrophysiologic study: VEP, ABR, SSEP. - clinical scales: 1. The Arabic version of the eight-item Morisky Medication Adherence Scale (MMAS-8). 2. Treatment Satisfaction Questionnaire for Medication (TSQM-9). 3. Extended disability status scale (EDSS) measurement for MS patients 4. Hamilton depression rating-17-item version (HAM-D 17). 5. Fatigue Severity Scale (FSS) for determination of fatigue degree using the Arabic validated version 6. The Pittsburgh Sleep Quality Index (PSQI) 7. International Restless Legs Syndrome rating scale time to diagnosis and DMT initiation was calculated and the rate of adherence was determined this was followed be determining factors related to each Data analysis was done using the IBM Statistical Package for Social Sciences software package version 20.0. (Armonk, NY: IBM Corp). The qualitative variables were described with ratio and percentage. The Shapiro-Wilk test was used to verify the normality of distribution. Quantitative variables with normal distribution were reported with mean and SD, and those without normal distribution were described using median and range of mid-quartiles. The level of statistical significance was set at p < 0.05. The used tests were 1. - Chi-square test: For categorical variables, to compare between different groups 2. - Monte Carlo correction: Correction for chi-square when more than 20% of the cells have expected count less than 5 3. - Mann Whitney test: For abnormally distributed quantitative variables, to compare between two studied categories 4. - Kruskal-Wallis test: For abnormally distributed quantitative variables, to compare between more than two studied categories 5. - Regression: univariate and multivariate logistic regression for factors related to delayed diagnosis, delayed treatment initiation and non-adherence ;
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