Rehabilitation of stroke patients with plegic hands: Randomized controlled trial of expanded Constraint-Induced Movement therapy
Bibliographic record
Abstract
PURPOSE: To evaluate the efficacy of an expanded form of Constraint-Induced Movement Therapy (eCIMT) that renders CIMT, originally designed for treating mild-to-moderate upper-extremity hemiparesis, suitable for treating severe hemiparesis. METHODS: Twenty-one adults ≥1 year after stroke with severe upper-extremity hemiparesis (with little or no capacity to make movements with the more-affected hand) were randomly assigned to eCIMT (n = 10), a placebo-control procedure (n = 4), or usual care (n = 7). The participants who received usual care were crossed over to eCIMT four months after enrollment. The CIMT protocol was altered to include fitting of orthotics and adaptive equipment, selected neurodevelopmental techniques, and electromyography-triggered functional electrical stimulation. Treatment was given for 15 consecutive weekdays with 6 hours of therapy scheduled daily for the immediate eCIMT group and 3.5 hours daily for the cross-over eCIMT group. RESULTS: At post-treatment, the immediate eCIMT group showed significant gains relative to the combination of the control groups on the Grade-4/5 Motor Activity Log (MAL; mean = 1.5 points, P < 0.001, f = 4.2) and a convergent measure, the Canadian Occupational Performance Measure (COPM; mean = 2.3, P = 0.014, f = 1.1; f values ≥0.4 are considered large, on the COPM changes ≥2 are considered clinically meaningful). At 1-year follow-up, the MAL gains in the immediate eCIMT group were only 13% less than at post-treatment. The short and long-term outcomes of the crossover eCIMT group were similar to those of the immediate eCIMT group. CONCLUSIONS: This small, randomized controlled trial (RCT) suggests that eCIMT produces a large, meaningful, and persistent improvement in everyday use of the more-affected arm in adults with severe upper-extremity hemiparesis long after stroke. These promising findings warrant confirmation by a large RCT.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".