Predictors of training-related improvement in visuomotor performance in patients with multiple sclerosis: A behavioural and MRI study.
Mult Scler
; 27(7): 1088-1101, 2021 06.
Article
in En
| MEDLINE
| ID: mdl-32749927
ABSTRACT
BACKGROUND:
The development of tailored recovery-oriented strategies in multiple sclerosis requires early identification of an individual's potential for functional recovery.OBJECTIVE:
To identify predictors of visuomotor performance improvements, a proxy of functional recovery, using a predictive statistical model that combines demographic, clinical and magnetic resonance imaging (MRI) data.METHODS:
Right-handed multiple sclerosis patients underwent baseline disability assessment and MRI of the brain structure, function and vascular health. They subsequently undertook 4 weeks of right upper limb visuomotor practice. Changes in performance with practice were our outcome measure. We identified predictors of improvement in a training set of patients using lasso regression; we calculated the best performing model in a validation set and applied this model to a test set.RESULTS:
Patients improved their visuomotor performance with practice. Younger age, better visuomotor abilities, less severe disease burden and concurrent use of preventive treatments predicted improvements. Neuroimaging localised outcome-relevant sensory motor regions, the microstructure and activity of which correlated with performance improvements.CONCLUSION:
Initial characteristics, including age, disease duration, visuo-spatial abilities, hand dexterity, self-evaluated disease impact and the presence of disease-modifying treatments, can predict functional recovery in individual patients, potentially improving their clinical management and stratification in clinical trials. MRI is a correlate of outcome, potentially supporting individual prognosis.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Multiple Sclerosis
Type of study:
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
Language:
En
Journal:
Mult Scler
Journal subject:
NEUROLOGIA
Year:
2021
Document type:
Article