Lost Time, Lost Function? Unraveling the Impact of Diagnosis Delay on Disability Progression in Multiple Sclerosis

Introduction:

Multiple Sclerosis (MS) is an autoimmune demyelinating disease of the central nervous system (CNS) with inflammatory and neurodegentative components and is the most common nontraumatic disabling neurologic condition is young adults. Prevalence of MS has increased in recent decades, with greater life expectancy and functionality being attributed to a better understanding of the disease and its early diagnosis.

Objective:

To correlate the delay in diagnosis and the onset of the first symptom with the Expanded Disability Status Scale (EDSS).

Methods:

An observational study was performed, with 199 patients analyzed through chart review of patients from the Demyelinating Outpatient Clinic, from July to December 2023.

Using data from the table, two groups were separated: time from the first symptom to diagnosis and time from the first symptom to the start of follow-up. In this sense, a comparison was made with the value of the EDSS and the number of years that patients took to start follow-up or receive the diagnosis.

After tabulation, inferential and exploratory data analysis was performed. All analysis were performed using SPSS version 20.0.0. Statistical significance was established at p<0.05.

Results:

Using the Spearman's rank correlation coefficient, it was obtained that the group of time to diagnosis and first symptom presented a coefficient of +0.277 (p<0.05), while time of symptoms and follow-up presented a value of +0.337 (p<0.05).

Conclusion:

Although the correlation is intuitive, the data analyzed in our study evidenced a weak relationship between these variables, and this result might be attributed to 2 important limitations of the study: the intervals were counted in years, not in months, and the EDSS scale was applied by different examiners using different methodologies. Therefore, it is necessary to broaden the scope of this study, aiming for better correction of variables and potential biases.