BackgroundFunctional biomarkers able to identify multiple sclerosis (MS) patients at high risk of fast disability progression are lacking. The aim of this study was to evaluate the ability of multimodal (upper and lower limbs motor, visual, lower limbs somatosensory) evoked potentials (EP) to monitor disease course and identify patients exposed to unfavourable evolution.MethodsOne hundred MS patients were assessed with visual, somatosensory and motor EP and rated on the Expanded Disability Status Scale (EDSS) at baseline (T0) and about 6 years later (T1). The Spearman correlation (rS) was used to evaluate the relationship between conventional EP scores and clinical findings. Multiple (logistic) regression analysis estimated the predictive value of baseline electrophysiological data for three clinical outcomes: EDSS, annual EDSS progression, and the risk of EDSS worsening.ResultsIn contrast to longitudinal correlations, cross-sectional correlations between the different EP scores and EDSS were all significant (0.33 ≤ rS < 0.67, p < 0.001). Baseline global EP score and EDSS were highly significant predictors (p < 0.0001) of EDSS progression 6 years later. The baseline global EP score was found to be an independent predictor of the EDSS annual progression rate (p < 0.001), and of the risk of disability progression over time (p < 0.005). Based on a ROC curve determination, we defined a Global EP Score cut off point (17/30) to identify patients at high risk of disability progression illustrated by a positive predictive value of 70 %.ConclusionThis study provides a proof of the concept that electrophysiology could be added to MRI and used as another complementary prognostic tool in MS patients.Electronic supplementary materialThe online version of this article (doi:10.1186/s12883-016-0608-1) contains supplementary material, which is available to authorized users.

Background: Simultaneous execution of motor and cognitive tasks can result in worsened performance on one or both tasks, indicating cognitive motor interference (CMI). A growing amount of research on CMI in persons with Multiple Sclerosis (pwMS) is observed. However, psychometric properties of dual-task outcomes have been scarcely reported.Objective: To investigate the between-day test-retest reliability of the motor and cognitive dual-task costs (DTC) during multiple CMI test conditions with various task complexity in pwMS and matched healthy controls (HC).Methods: 34 pwMS (Expanded Disability Status Scale score 3.0±0.8) and 31 HCs were tested and retested on three single cognitive, four single motor and twelve cognitivemotor dual-tasks. Cognitive tasks included serial subtraction by seven, titrated digit span backwards and auditory vigilance. Motor tasks were walking: at self-selected speed, over obstacles, crisscross and while carrying a water-filled cup. Outcome measures were cognitive and motor DTC, calculated as percentage change of dualtask performance compared to single-task performance. Intraclass correlations (ICCs) and Spearman correlation coefficients were calculated as appropriate.Results: For DTCmotor of gait speed, ICCs ranged from 0.45 to 0.81 and Spearman correlations from 0.74 to 0.82. For DTCcognitive, ICCs ranged from -0.18 to 0.49 and Spearman correlations from -0.28 to 0.26. Reliability depended on the type of motor and cognitive task.Conclusion: Reliability of the DTCmotor was, overall, good, while that of the DTCcognitive was poor. The 'walking' and 'cup' dual-task conditions were the most reliable regardless of the integrated cognitive task.3

Background: Cognitive–motor interference (CMI) has been well recognized in persons with multiple sclerosis (pwMS); however, there are limited data on effects of task difficulty. Objective: Examine (1) the effects of motor and cognitive tasks varying in difficulty on the magnitude of CMI and (2) the discriminative validity of CMI between pwMS and healthy controls (HC). Methods: Nine cognitive–motor dual-task (DT) conditions (combinations of three cognitive and three walking tasks) were examined. Outcome measures were DT-performance and dual-task cost (DTC) of gait parameters and correct answers. Task differences and overall group-effects were analysed by mixed model analysis, plus the Wilcoxon signed-rank tests or multivariate analysis of variances (MANOVAs), respectively. Results: Task effects were examined in 82 pwMS (Expanded Disability Status Scale (EDSS): 3.3 ± 1.0) and discriminative validity in a subsample (35 pwMS and 33 HC). Motor-DTC and DT-performance were affected by difficulty of both the cognitive task ( p < 0.001) and the walking condition ( p ⩽ 0.002), while cognitive-DTC only varied between cognitive tasks with a large difference in difficulty ( p ⩽ 0.005) and not between walking conditions ( p ⩾ 0.125). None of the DTCs differed between groups. Conclusion: CMI, and especially motor performance, is affected by difficulty of the DT. Although pwMS performed worse on the tasks than HC, none of the DT-conditions showed a discriminative DTC.

The clinical variability and complexity of multiple sclerosis (MS) challenges the individual clinical course prognostication. This study aimed to find out whether multimodal evoked potentials (EP) correlate with the motor components of multiple sclerosis functional composite (MSFCm) and predict clinically relevant motor functional deterioration. One hundred MS patients were assessed at baseline (T ) and about 7.5 years later (T), with visual, somatosensory and motor EP and rated on the Expanded Disability Status Scale (EDSS) and the MSFCm, including the 9 Hole Peg Test and the Timed 25 Foot Walk (T25FW). The Spearman correlation coefficient (r ) was used to evaluate the cross-sectional and longitudinal relationship between EP Z scores and clinical findings. The predictive value of baseline electrophysiological data for clinical worsening (EDSS, 9-HPT, T25FW, MSFCm) during follow-up was assessed by logistic regression analysis. Unlike longitudinal correlations, cross-sectional correlations between EP Z scores and clinical outcomes were all significant and ranged between 0.22 and 0.67 (p< 0.05). The global EP Z score was systematically predictive of EDSS and MSFCm worsening over time (all p < 0.05). EP latency was a better predictor than amplitude, although weaker than latency and amplitude aggregation in the global EP Z score. The study demonstrates that EP numerical scores can be used for motor function monitoring and outcome prediction in patients with MS.

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