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BackgroundIn chronic neurological diseases, especially in multiple sclerosis (MS), clinical assessment of motor dysfunction is crucial to monitor the disease in patients. Traditional scales are not sensitive enough to detect slight changes. Video recordings of patient performance are more accurate and increase the reliability of severity ratings. When these recordings are automated, quantitative disability assessments by machine learning algorithms can be created. Creation of these algorithms involves non–health care professionals, which is a challenge for maintaining data privacy. However, autoencoders can address this issue. ObjectiveThe aim of this proof-of-concept study was to test whether coded frame vectors of autoencoders contain relevant information for analyzing videos of the motor performance of patients with MS. MethodsIn this study, 20 pre-rated videos of patients performing the finger-to-nose test were recorded. An autoencoder created encoded frame vectors from the original videos and decoded the videos again. The original and decoded videos were shown to 10 neurologists at an academic MS center in Basel, Switzerland. The neurologists tested whether the 200 videos were human-readable after decoding and rated the severity grade of each original and decoded video according to the Neurostatus-Expanded Disability Status Scale definitions of limb ataxia. Furthermore, the neurologists tested whether ratings were equivalent between the original and decoded videos. ResultsIn total, 172 of 200 (86.0%) videos were of sufficient quality to be ratable. The intrarater agreement between the original and decoded videos was 0.317 (Cohen weighted kappa). The average difference in the ratings between the original and decoded videos was 0.26, in which the original videos were rated as more severe. The interrater agreement between the original videos was 0.459 and that between the decoded videos was 0.302. The agreement was higher when no deficits or very severe deficits were present. ConclusionsThe vast majority of videos (172/200, 86.0%) decoded by the autoencoder contained clinically relevant information and had fair intrarater agreement with the original videos. Autoencoders are a potential method for enabling the use of patient videos while preserving data privacy, especially when non–health-care professionals are involved.

Background: Improving health-related quality of life (HRQoL) is an important disease management goal in persons with Multiple Sclerosis (PwMS). HRQoL decreases with increasing age and prolonged disease duration; other factors remain less understood. Objective: To identify associations of multiple sclerosis (MS) disease characteristics and symptom burden with low HRQoL. Methods: Using the Swiss MS Registry, we applied quantile regression adjusted for age and MS disease duration to determine 25th (low HRQoL) and 75th (high HRQoL) percentiles of the EuroQol-5-Dimension (EQ-5D) distribution for PwMS. We compared PwMS across HRQoL groups by analyzing differences in sociodemographics, symptom burden, MS risk factors, gait impairment, and the MS Severity Score (MSSS), all measured at the same time as HRQoL. The analyses included descriptive methods, multivariable multinomial regression, and simultaneous quantile regression as a sensitivity analysis. Results: We included 1697 PwMS with median age and time-to-diagnosis of 49 and 9 years. Multivariable regression revealed low HRQoL to be associated with receiving invalidity insurance benefits, reporting depression, muscle weakness, memory problems, pain, and severe gait impairment. The analysis for individuals with available MSSS (n = 937) showed an increasing probability of low HRQoL with higher MSSS. Conclusion: Our segmentation method identified symptom burden and MS severity as factors associated with low HRQoL. Pharmacological and non-pharmacological MS symptom management, especially for depression, fatigue, pain, and muscle weakness, may warrant increased attention to preserve or improve HRQoL. [ABSTRACT FROM AUTHOR]

Background: Although healthcare practitioners (HCPs) are a valuable source of social support, research on support provided by neurologists to older persons with multiple sclerosis (pwMS) remains limited. Objectives: To explore expectations of pwMS aged 55 years or older regarding MS care and to identify support types, met and unmet needs within their relationship with neurologists. Methods: Utilizing a mixed-methods approach, we analyzed survey data from Swiss Multiple Sclerosis Registry participants. Quantitative data included Likert scales gauging the importance of various aspects of MS care for pwMS both in and out of neurological care. Qualitative data were derived from three open-ended questions, focusing on neurologist-provided support for pwMS in neurological care. Data underwent descriptive and deductive thematic analysis, using Cutrona and Suhr framework for coding social support. Results: Among the 286 participants (median age 61.0 years, interquartile range (IQR) 57.0–66.0; median disease duration 23.5 years, IQR 15.0–31.0), 84.6% (N = 244) were under neurological care. Quantitative findings highlighted the significance of HCP expertise and consultation time. Qualitative analysis identified all social support domains in the neurologist–pwMS relationship, with informational support being most prevalent, followed by emotional support. Neurologists' expertise, availability, comprehensive advising, listening, and validation emerged as key themes. Unmet needs were relatively infrequent and concerned insufficient information on complementary medicine, empathy, and understanding of symptoms like fatigue. Conclusions: Older pwMS see neurologists as adequate providers of comprehensive support and particularly value neurologists' sufficient availability, informational and emotional support. Areas for improvement include attention to complementary medicine and empathy. [ABSTRACT FROM AUTHOR]

Mobile health applications (mHealth apps) may lead to health benefits. In recent years, the use of apps in multiple sclerosis (MS) has increased. Apps to train and improve dexterity in MS are scarce. This study investigated the effectiveness of a tablet app-based home-based training to improve dexterity in individuals with MS. In a randomized controlled trial, two standardized 4-week home-based interventions focussing on different aspects of dexterity and upper limb function were compared. Assessments were done at baseline, post-intervention and 12-week follow-up. The primary endpoint was the Arm Function in Multiple Sclerosis Questionnaire, a dexterity-related measure of patient-reported activities of daily living. Secondary endpoints were dexterous function, grip strength and health-related quality of life. Forty-eight individuals were randomly assigned to a tablet app-based program (n = 26) or a control strengthening exercise program (n = 22). No significant differences were found for the primary endpoint (p = 0.35). Some significant differences in favour of the app-group were found in fine coordinated finger movements and strength. No significant differences were found at the 12-week follow-up for all endpoints. Adherence in both groups was above 90%. App-based training was not superior compared to a control strengthening exercise program concerning the arm- and hand function from the participant's perspective. However, app-based training was found to be effective in improving specific dimensions (finger movements and strength), and can easily be applied at home. Therefore, individuals living with MS with impaired dexterity should consider app-based training. Clinicaltrials.gov NCT03369470. This study provides initial evidence for the effectiveness of a home-based app-based program for improving dexterous function in individuals living with multiple sclerosis through the implementation of a tablet app-based dexterity training. App-based training was not superior compared to a control strengthening exercise program concerning the arm- and hand function from the participant's perspective. Patients attending the app-based dexterity program showed some statistically significant improvements in fine coordinated finger movements and strength. [ABSTRACT FROM AUTHOR]

Multiple sclerosis (MS), particularly relapsing MS (RMS), has become a treatable disease in recent decades, and immunotherapies are now able to influence long-term disease course. A wide range of disease-modifying drugs are available, which makes the choice of therapy in individual cases considerably more complex. Due to specific regulatory aspects (partly diverging approvals by Swissmedic compared to the European Medicines Agency (EMA), and an independent evaluation process for the Federal Office of Public Health (FOPH) specialities list (SL)), we issued a consensus recommendation regarding specific aspects of immunotherapy for MS in Switzerland in 2019. Here, we present revised recommendations with an update on newly approved drugs and new safety aspects, also in reference to the risk of COVID-19 infection and vaccination. [ABSTRACT FROM AUTHOR]