A Phase 1 Exercise Dose Escalation Study for Stroke Survivors with Impaired Walking
Bibliographic record
Abstract
BACKGROUND: Targeted exercise and increased practice can improve the mobility of stroke survivors. However, many stroke survivors continue to have reduced physical work capacity and impaired walking, and experience frequent falls after participating in physical rehabilitation programs. AIM: In this Phase 1 study, we used a dose escalation method, common in pharmaceutical trials, to determine the maximum tolerable dose of multimodal exercise in community-dwelling stroke survivors with mobility impairment. METHODS: Stroke survivors 14-59 months poststroke participated in a 12-week (36 sessions) multimodal exercise program implemented using a cumulative 3 + 3 dose escalation design (featuring increasing doses in successive cohorts of three participants), with set dose-limiting tolerance criteria. The exercise intervention included challenging balance activities, strength, and endurance training. The program was individualized and focused on task-specific requirements for walking in the community. RESULTS: Six survivors participated before escalation was ceased. Four participants were able to tolerate up to 10·5 h/week of exercise, which included 283 min of endurance, 182 min of task practice, 138 min of strengthening, and 28 min resting. The program led to increased walking distance (Six-Minute Walk Test) and faster mobility (4 Square Step Test, Timed Up and Go Test), with pre-postimprovements averaging 23-41%. CONCLUSIONS: This is the first multimodal exercise dose escalation study in stroke. The maximal dose of exercise identified was dramatically higher than the dose typically delivered to stroke survivors in current trials. We now plan to confirm safety and feasibility of this program in a larger Phase II trial.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".