Ankle dysfunction in multiple sclerosis and the effects on walking
Bibliographic record
Abstract
PURPOSE: Even in the early stage of the disease, for patients suffering from multiple sclerosis (MS), the most common and reported biomechanical alterations in the lower limb are located at the ankle joint. However, the effects of these impairments on gait deterioration should be discussed. MATERIALS AND METHODS: This review was written according to the PRISMA guidelines. The search focussed on biomechanical changes (kinetic, kinematic, and electromyographic data) at the ankle during gait in MS patients. The search was performed in the databases: Pubmed, Web of Science, and Cochrane Library. RESULTS: Eleven studies were included. The reduction in the ankle range of motion (RoM) induced by increased cocontractions of the tibialis anterior and triceps surae muscles could be a compensatory strategy to improve body-weight support and balance during the stance phase. CONCLUSIONS: Future rehabilitation programmes should consider the control of weight support at the ankle during gait training.Implications for rehabilitationThe ankle supports and stabilises the body during the stance phase of gait.The reduced ankle range of motion in multiple sclerosis (MS), even at an early stage of the disease, is due to cocontractions of tibialis anterior and triceps surae and could be a compensatory strategy to be more stable.Rehabilitation programmes for MS patients should focus on the control of body segments motion during the weight transfer above the ankle.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".