Dual Effects of Body-Weight Supported Treadmill Training on Cardiovascular Fitness and Walking Ability Early After Stroke
Bibliographic record
Abstract
BACKGROUND: Body-weight-supported treadmill training (BWSTT) to train both fitness and ambulation has not been investigated. OBJECTIVE: To compare the effectiveness of BWSTT to dose-equivalent usual care (UC) in improving cardiovascular fitness and walking early after stroke. METHODS: Participants were randomly assigned to 1 of 2 interventions: BWSTT + UC or UC. All individuals participated in 60-minute physiotherapy sessions 5 times weekly as inpatients for 6 weeks and 3 times weekly as outpatients for another 6 weeks. Baseline, posttraining, 6-, and 12-month follow-up outcome measures were as follows: primary, fitness (peak oxygen consumption, VO2peak) and walking ability (6-Minute Walk Test [6MWT] and 10-m walk); secondary, Berg Balance Scale (BBS) and motor impairment (Chedoke-McMaster Stages of Recovery [CMSR] Leg and Foot). RESULTS: In all, 50 individuals (mean age, 60 ± 14 years; mean event-to-randomization, 23 ± 5 days; 29 men) participated. No adverse events occurred. BWSTT improved VO2peak by 30%, which was significantly greater than the 8% improvement observed for UC (P = .004 between groups). Similarly, there were significant Time × Group interactions for 6MWT and CMSR Foot, with BWSTT outperforming UC for gains in distance (P = .15; 48% vs. 19%, respectively) and stage (P = .01; 1.0 vs. 0.3, respectively). No group effect was seen for 10-m walk speed, BBS, or CMSR Leg, with both groups demonstrating significant gains. In general, gains observed were preserved for 12 months. CONCLUSIONS: BWSTT elicits greater improvements in cardiovascular fitness and walking endurance than UC in the subacute poststroke period. These gains are largely sustained for 1 year.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".