Training to achieve over ground walking after spinal cord injury: A review of who, what, when, and how
Bibliographic record
Abstract
OBJECTIVES: (1) To provide clinicians with the best evidence for effective retraining of walking after spinal cord injury (SCI) to achieve over ground walking. (2) To identify gaps in our knowledge to guide future research. METHODS: Articles that addressed the retraining of walking in adults with SCI and reported outcome measures of over ground walking ability were identified through a non-systematic search of the PubMed, Scopus, and CINAHL databases. No restriction was applied to the method of training. Selected articles were appraised using the Physiotherapy Evidence Database scale. Information was synthesized to answer who best responds to what type of treatment, how that treatment should be delivered, and at what stage after injury. RESULTS: Individuals with motor incomplete SCI (American Spinal Injury Association (ASIA) Impairment scale (AIS) C and D) are most likely to regain walking over ground. The effective methods of training all involved a substantial component of walking in the training, and if assistance was provided, partial assistance was more effective than total assistance. Walking training resulted in a change in over ground walking speed of 0.06-0.77 m/s, and 6 minute walk distance of 24-357 m. The effective training schedules ranged from 10 to 130 sessions, with a density of sessions ranging from 2 per week to 5 per week. Earlier training led to superior results both in the subacute (<6 months) and chronic phases (>6 months) after injury, but even individuals with chronic injuries of long duration can improve. CONCLUSIONS: Frequent, early treatment for individuals with motor incomplete SCI using walking as the active ingredient whether on the treadmill or over ground, generally leads to improved walking over ground. Much work remains for the future, including better quantification of treatment intensity, better outcome measures to quantify a broader range of walking skills, and better ways to retrain individuals with more severe lesions (AIS A and B).
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".