Commentary to: Task-specific and impairment-based training improve walking ability in stroke
Bibliographic record
Abstract
Question: Is a task-specific locomotor training program (LTP) or impairment-based strength and balance home exercise program (HEP) better at improving walking function in people with stroke than usual care (UC)?Design: Multicentre randomised controlled trial with blinded outcome assessment.Setting: Six rehabilitation units in the USA.Participants: Key inclusion criteria were: adults, within 45 days of stroke, with a self-selected gait speed of < 0.8 m/s and living in the community by the time of randomisation.Key exclusion criteria were exercise contraindications.Randomisation of 408 participants allocated 139, 126 and 143 individuals to the LTP, HEP, and UC respectively.Interventions: Both the LTP and HEP groups received supervised training three days per week for 12 to 16 weeks.The locomotor training program included locomotor training on a treadmill with partial bodyweight support and overground walking practice in an outpatient facility.The home exercise program consisted of strength and balance exercises supervised in the home.Outcome measures: The primary outcomes were the proportion of people who were able to achieve a functional walking level, which was defined as a walking speed of > 0.4 m/s for those whose initial speed was < 0.4 m/s, or J o u r n a l o f PHYSIOTHERAPY
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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 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.072 | 0.046 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".