Constraint-Induced Movement Therapy for Severe Upper-Extremity Impairment after Stroke in an Outpatient Rehabilitation Setting: A Case Report
Bibliographic record
Abstract
PURPOSE: Laboratory studies confirm that constraint-induced movement therapy (CIMT) improves upper-extremity (UE) function after stroke. Due to strict patient criteria and the intensive resources required, CIMT has been slow to become part of rehabilitation practice. Our purpose was to determine the feasibility and effectiveness of an adapted experimental protocol within an outpatient clinical setting for a patient with moderate to severe UE impairment who did not meet traditional CIMT criteria. PATIENT DESCRIPTION: AJ, a 16-year-old male, experienced a left middle cerebral artery ischemic stroke due to carotid artery dissection one year before beginning CIMT. He demonstrated some proximal movement but no wrist or finger extension. He had received intensive rehabilitation for 12 months prior to beginning CIMT. INTERVENTION: Two occupational therapists and two physiotherapists collaborated to provide CIMT task training for 6 hours daily for 2 weeks. A knitted mitten extending to the elbow restrained the less-involved UE during 90% of waking hours. Tasks were tailored to AJ's interests, with the goal of integrating his affected UE into his behavioural repertoire. MEASURES AND OUTCOMES: After 2 weeks of CIMT, AJ improved in all measures (grip and lateral pinch strength, Action Research Arm Test [ARAT], and Box and Block Test) except the Chedoke McMaster Impairment Inventory. Greatest gains were seen at 6 months in the ARAT and Box and Block Test, which coincided with patient and family reports of AJ's using his arm in everyday functional tasks. IMPLICATIONS: Shared workload, emphasis on relevant functional tasks, and complete family participation likely influenced the success of CIMT. Our findings suggest that the strict CIMT criteria used in previous studies may exclude patients who might benefit from the treatment. Controlled trials should be undertaken to examine the effects of CIMT in patients with moderate to severe UE impairment.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".