Case Report: Physical therapy management of axial dystonia
Bibliographic record
Abstract
Few studies have described physical therapy approaches to provide functional independence and reduce pain in individuals with dystonia. This report describes the physical therapy treatment of a 46-year-old woman diagnosed with idiopathic segmental axial dystonia. For two years, the patient was treated with kinesiotherapy (active and resisted movements and stretching of neck and trunk muscles), abdominal taping (kinesiotaping techniques), functional training, and sensory tricks. She was assessed with parts I, II and III of Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS-I, TWSTRS-II and TWSTRS-III), Berg Balance Scale (BBS), Six-Minute Walk Test (6-MWT), and the motor domain of Functional Independence Measure (FIM-motor) before and after the two-year treatment and after the one year follow-up. Postural control and symmetry improved (TWSTRS-I: from 30 to 18), functional independence increased (TWSTRS-II: from 27 to 15; BBS: from 36 to 46; 6-MWT: from 0 to 480 meters (m); FIM-motor: from 59 to 81), and the pain diminished (TWSTRS-III: from 12 to 5). The functional improvement was retained after one year (TWSTRS-I: 14/35; TWRTRS-II: 12/30; TWRTRS-III: 5/20; BBS: 48/56; 6-MWT: 450 m; FIM-motor: 81/91). This program showed efficacy on providing a better control of the dystonic muscles and thus the doses of botulinum toxin needed to treat them could be reduced. Outcomes support the therapeutic strategies used to deal with this type of dystonia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".