ABSTRACT
Timely diagnosis of multiple sclerosis (MS) is a challenge due to factors such as prompt identification of symptoms and consequent delays in hospital visits and treatment initiation. In part to address this challenge, an expert scientific advisory panel of clinical nurse practitioners (CNPs) from different European nations was convened by Viatris on October 25, 2022, in Amsterdam, the Netherlands. This meeting was an interactive discussion to understand the role of clinical nurse practitioners in MS management. The objectives were to (1) understand the current delays in MS diagnosis from the perspective of expert CNPs; (2) determine the role of the CNP in MS management; and (3) identify the opportunities to improve accessibility, foster collaboration among stakeholders, and promote initiatives to educate people with MS. The recommendations of the panel underline the multidimensional role of CNPs in the management of MS at all stages. Health care stakeholders need to work together to achieve better access to treatment regimens and facilitate outcomes in the management of MS through shared decision-making and follow-ups. Further exploration of the role of CNPs in the management of MS, as well as recommendations for early diagnosis, will help both general practitioners and specialists better manage MS care.
ABSTRACT
A BACKROUND: Multiple sclerosis (MS) is a complex chronic disease of the central nervous system (CNS). Body mass index (BMI), a component of metabolic syndrome (MetS), is considered among the risk factors for MS. However, its role in MS remains ambiguous. OBJECTIVE: To examine the impact of BMI on the age of onset in patients with relapsing-remitting MS (RRMS) in a Greek cohort. METHODS: Data from 821 Greek patients with RRMS were collected. The BMI values were considered as quartiles. Comparisons for the demographic characteristics between the quartiles were made by Pearson's chi-square test for the categorical variables and by ANOVA for the continuous variables. An overall p-value was calculated corresponding to trend for association. In case of significant association, further post-hoc analysis was performed in order to identify differences in demographic characteristics between specific BMI quartiles groups. Linear regression analyses were used to assess the relationship between BMI and age at onset of MS. RESULTS: Comparisons of participant characteristics by quartiles of BMI revealed that participants with the highest BMI had an older age of disease onset. Results from linear regression analysis showed that with each increase of 1 BMI unit, the age of RRMS onset increases by 0.255 (95% CI 0.136 to 0.374) years, p < 0.001. CONCLUSIONS: Patients with higher BMI, as a parameter of MetS, exhibit increased age of RRMS onset. Our results may present an alternative personalized approach for diagnosis, prognosis, and/or prevention of RRMS.