Efficacy of Incobotulinum toxin‐A for the treatment of masseter muscle hypertrophy in Asian Indian patients: A 2‐year follow‐up study
Bibliographic record
Abstract
BACKGROUND: ; Merz Pharma Canada Ltd., Burlington, ON, Canada) are a preferred modality for reducing the volume of the muscle and therefore reducing the width of masseter. AIMS: To evaluate the efficacy of Xeomin treatment in long-term management of bilateral masseter hypertrophy in Asian Indian patients. PATIENTS/METHODS: A total of 30 patients were enrolled in the study and were injected with 30 U Xeomin on each side of face, at baseline. Fifteen patients received a second session of Xeomin injection at 12th week, and remaining 15 patients received an additional third session, at 12th and 24th weeks post the first injection, respectively. Follow-up was done at 4th-, 12th-, 24th-, and 36th-week and at first- and second-year follow-ups. RESULTS: For the patients who received two injections, the maximum reduction of 26.85% was observed at 24th week, which was maintained as 20.04% reduction until second follow-up year. The patients who received three injections exhibited very high reduction of 43.12% of masseter volume at 36th week, which was maintained at 38.72 % until the second follow-up year. Three sessions of Xeomin injections were proved to be more effective in long-term maintenance of reduced masseter volume than 2 sessions of injections. CONCLUSIONS: Xeomin injections were found to be effective in long-term management of bilateral masseter hypertrophy. This is the first of its kind paper, which evaluates the long-term effects of Xeomin injections for the treatment of masseter hypertrophy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".