The effectiveness of using a centrally acting muscle relaxant in combination with botulinum toxin injections in patients with spasmodic torticollis
Bibliographic record
Abstract
Objective. To analyze the efficacy of eperison in combination with botulinum toxin injections for the treatment of pain syndrome in patients with spastic torticollis (ST). Material and methods. A retrospective study was conducted to evaluate the effectiveness of eperison administration alongside botulinum therapy in 29 patients diagnosed with ST. The study employed a cross-sectional retrospective analysis of medical data. Patients receiving botulinum toxin injections at three-month intervals (a total of 6 cycles), with assessments at 2 months (4—6 cycles after each injection), were administered eperison at a dose of 150 mg/day. The efficacy of the treatments was evaluated using a validated scale: the 85-point TWSTRS (Toronto Western Spasmodic Torticollis Rating Scale), assessed three times—before each botulinum injection (on day 1), at day 14, and and at day 60 later. Results. For cycles 1—3 (botulinum toxin, without eperisone), the average TWSTRS scale score on the on day 1 of each cycle was 40.72 — 41.66; cycles 4—6 with the addition of Eperisone — 26.6—30.4 points. When comparing the average values of the TWSTRS scale for cycles 1—3 and cycles 4—6 on the «Pain» scale, t-test value was: 15.85 (p=0.000546). Conclusion. The intake of the centrally acting muscle relaxant eperison resulted in a statistically significant improvement in patients with ST by the time of the next injection (paired Student’s t-test 2.77—2.92, p=0.05), including improvements in the «Pain» scale, compared to botulinum therapy without eperison in the same patients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 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".