Onset Symptom Clusters in Multiple Sclerosis: Characteristics, Comorbidities, and Risk Factors.

ABSTRACT: Background: Multiple sclerosis (MS) symptoms are expected to aggregate in specific patterns across different stages of the disease. Here, we studied the clustering of onset symptoms and examined their characteristics, comorbidity patterns and associations with potential risk factors. Methods: Data stem from the Swiss Multiple Sclerosis Registry, a prospective study including 2,063 participants by November 2019. MS onset symptoms were clustered using latent class analysis (LCA). The latent classes were further examined using information on socio-demographic characteristics, MS-related features, potential risk factors, and comorbid diseases. Results: The LCA model with six classes (frequencies ranging from 12 to 24%) was selected for further analyses. The latent classes

SUBMITTER: Ajdacic-Gross V 

PROVIDER: S-EPMC8290323 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature