Strengthening to Promote Functional Recovery Poststroke: An Evidence-Based Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Following stroke, patients/clients suffer from significant impairments. However, weakness is the predominant common denominator. Historically, strengthening or high-intensity resistance training has been excluded from neurorehabilitation programs because of the concern that high-exertion activity, including strengthening, would increase spasticity. Contemporary research studies challenge this premise. METHOD: This evidence-based review was conducted to determine whether high-intensity resistance training counteracts weakness without increasing spasticity in persons poststroke and whether resistance training is effective in improving functional outcome compared to traditional rehabilitation intervention programs. The studies selected were graded as to the strength of the recommendations and the levels of evidence. The treatment effects including control event rate (CER), experimental event rate (EER), absolute risk reduction (ARR), number needed to treat (NNT), relative benefit increase (RBI), absolute benefit increase (ABI), and relative risk (RR) were calculated when sufficient data were present. RESULTS: A total of 11 studies met the criteria. The levels of evidence ranged from fair to strong (3B to 1B). CONCLUSIONS: Despite limited long-term follow-up data, there is evidence that resistance training produces increased strength, gait speed, and functional outcomes and improved quality of life without exacerbation of spasticity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it