Symptom-Level Disability Status Assessed with an Electronic Unsupervised Patient-Reported Expanded Disability Status Scale (ePR-EDSS) in Multiple Sclerosis Patients—The Example of Croatia

The present study aimed to apply an electronic, unsupervised patient-reported Expanded Disability Status Scale (ePR-EDSS) to investigate disability severity in people with multiple sclerosis (pwMS) as a case study in Croatia in 2021, including demographic and comorbidity characteristics and multiple sclerosis (MS) disease-related factors. The cross-sectional study was conducted as an online survey from 4 October 2021 to 31 December 2021. Symptom-level disability status was assessed with ePR-EDSS for MS capturing MS-related disability across the spectrum of severity.The study enrolled 147 pwMS patients, of which 84% were women. The mean age ± standard deviation in the sample was 41.1 ± 11.3, and the mean disease duration was 8.5 ± 7.4 years, with a median EDSS score of 3.0 (range, 0–8). The distribution of the participants according to clinical forms of MS was as follows: 71% had relapsing-remitting MS, 13% had primary progressive MS, 4% had secondary progressive PMS, and 12% did not provide information on their MS type. Twenty-nine point two percent (29.2%) of the participants had comorbidities in addition to MS. EDSS scores indicate significant differences with regard to age (t = −3.51, p < 0.001), gender (χ2 = 8.04, p < 0.01), and immunomodulatory drug use (χ2 = 5.89, p < 0.05). An ePR-EDSS analysis of disability symptoms showed a significant difference in symptoms with regard to strength, sensation, coordination, vision, fatigue, mobility, and overall wellness among MS types. Participants with PPMS and SPMS were older on average, had higher EDSS, and had more pronounced symptoms of disability measured with ePR-EDSS compared to those with RRMS. Application of ePR-EDSS shows it to be a reliable eHealth tool for clinical assessment of pwMS disability status, and future studies should correlate it with standard self-report scales capturing MS symptoms such as fatigue, depression, anxiety, and stress.