Current practices in the management of adductor spasmodic dysphonia.
Bibliographic record
Abstract
INTRODUCTION: Adductor spasmodic dysphonia (ADSD) is a focal dystonia treated most commonly by chemodenervation of the thyroarytenoid (TA) muscles with botulinum toxin. Currently, there are no consensus guidelines regarding this treatment and the management of ADSD. The objective of this study was to assess current practice patterns among physicians who treat ADSD. METHODS: A cross-sectional survey study was conducted regarding treatment choices and specific technical aspects of injection technique and botulinum toxin use. The study population consisted of laryngologists from the Canadian Society of Otolaryngology-Head and Neck Surgery and laryngologists obtained from the American Laryngological Association member database and the American Academy of Otolaryngology-Head and Neck Surgery Neurolaryngology Study Group. RESULTS: An overall response rate of 13% was achieved, with a high absolute number of physicians who manage ADSD responding (n = 37). Most respondents treat ADSD by injecting botulinum toxin type A (Botox) through the cricothyroid membrane submucosally at a mode starting dose of 2.5 units per TA muscle using electromyographic guidance with or without fibre-optic laryngoscopy every 3 to 4 months, with the frequency of reinjection being based on patient symptomatology. There is much variability with regard to starting injection dose, alternate treatments for ADSD, unilateral versus bilateral injections, and guidance technique. Most physicians (36 of 37) share one vial among more than one patient, and some (7 of 37) freeze a reconstituted vial that has remaining toxin for reuse at a later time. CONCLUSIONS: There is considerable variability in treatment practices for the management of ADSD. Further study is warranted to define an optimal therapeutic paradigm.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".