The Effects of Aerobic Exercise on the Recovery of Walking Ability and Neuroplasticity in People with Multiple Sclerosis: A Systematic Review of Animal and Clinical Studies
Bibliographic record
Abstract
INTRODUCTION: Walking is of high priority for people with multiple sclerosis (PwMS). It remains unclear whether aerobic exercise can improve walking ability and upregulate neurotrophins. This review aims to consolidate evidence to develop optimal aerobic training parameters to enhance walking outcomes and neuroplasticity in PwMS. METHODS: Clinical studies examining aerobic exercise for ≥3 weeks, having outcomes on walking with or without neurotrophic markers, were included. Studies utilizing animal models of MS were included if they employed aerobic exercise with outcomes on neurological recovery and neurotrophins. From a total of 1783 articles, 12 clinical and 5 animal studies were included. RESULTS: Eleven clinical studies reported improvements in walking ability. Only two clinical studies evaluated both walking and neurotrophins, and neither found an increase in neurotrophins despite improvements in walking. Patients with significant walking impairments were underrepresented. Long-term follow-up revealed mixed results. Two animal studies reported a positive change in both neurological recovery and neurotrophins. CONCLUSION: Aerobic exercise improves walking ability in PwMS. Gains are not consistently maintained at 2- to 9-month follow-up. Studies examining levels of neurotrophins are inconclusive, necessitating further research. Aerobic exercise enhances both neurological recovery and neurotrophins in animal studies when started 2 weeks before induction of MS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".