Longitudinal Effects of Botox Injections on Voice-Related Quality of Life (V-RQOL) for Patients With Adductory Spasmodic Dysphonia
Bibliographic record
Abstract
OBJECTIVE: To investigate the longitudinal effects of botulinum toxin type A (Botox) injections on voice-related quality of life (V-RQOL) for patients with adductory spasmodic dysphonia. DESIGN: Prospective study. SETTING: Academic tertiary care referral center. PARTICIPANTS: Forty-two patients who presented to our institution with dysphonia and were diagnosed as having adductory spasmodic dysphonia during a 38-month period. INTERVENTION: Patients received Botox injections into both thyroarytenoid muscles via the cricothyroid membrane. The typical starting dose was 1.0 U per vocal fold. If necessary, the dosage was adjusted in subsequent injections to reduce adverse effects or to enhance duration of benefit. MAIN OUTCOME MEASURES: Patients filled out questionnaires, including the V-RQOL Measure and a self-assessed overall voice rating, before each injection. Postinjection questionnaires were completed 6 to 8 weeks after each treatment. Mean pretreatment and posttreatment scores were calculated for each treatment. RESULTS: The number of treatments per patient ranged from 1 to 7. Statistically significant improvements in mean total and domain V-RQOL scores were calculated for every injection (P<.01) (no postinjection questionnaires were available for the seventh injections). The magnitude of the effect remained constant for later injections. Eighty-two percent of the population recorded at least 1 category of improvement in overall self-assessed voice rating with each injection. CONCLUSIONS: Botox has a significant beneficial effect on V-RQOL for at least 6 injection cycles. This study demonstrates the efficacy of Botox for treating patients with adductory spasmodic dysphonia and further illustrates the usefulness and validity of the V-RQOL Measure in evaluating patients with dysphonia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".