Alien hand syndrome: a case report and description to rehabilitation
Bibliographic record
Abstract
BACKGROUND: Alien hand syndrome (AHS) is a neurological disorder in which movements are performed against conscious will. It is rare but significant due to its disability impact on everyday life. This case highlights the clinical features, recovery course and response to rehabilitation of a patient with a dominant anterior cerebral artery territory infarct. METHODS: Single case report. RESULTS: Clinical signs and symptoms included right hemiparesis, hemianesthesia, dysphagia, language and cognitive dysfunction, personification and autonomous movement of the affected limb; involuntary grasping of objects interfered with his activities of daily living (ADL). Education for diagnosis and compensatory strategies of AHS, including visualisation, distraction of affected limb and maintaining a slow/steady pace with activities decreased the frequency of his AHS movements from 10 times to twice a day. Over the course of 4 months the rehabilitation treatment targeted toward the specific needs of the patient, allowed improvement in his ADL. Commonly used upper extremity motor recovery outcome measures like the Chedoke McMaster Stroke Assessment cannot be considered as a sensitive tool for AHS. More sensitive outcome measures are needed to be determined for this condition. CONCLUSION: This case distinguishes the clinical findings and description to rehabilitation in a case of AHS.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".