Early Postoperative Application of Botulinum Toxin Type A Prevents Hypertrophic Scarring after Epicanthoplasty: A Split-Face, Double-Blind, Randomized Trial
Bibliographic record
Abstract
BACKGROUND: Postoperative hypertrophic scarring of the medial canthal area is a common phenomenon and deterrent for patients considering epicanthoplasty. Botulinum toxin type A has been reported for hypertrophic scar and keloid treatment. However, there is a lack of high-level evidence regarding the effects of botulinum toxin type A in the medial canthal area. METHODS: In this split-face, double-blind, randomized trial, 43 consecutive consenting patients undergoing Park Z-epicanthoplasty were randomized to receive 5 U of botulinum toxin type A or the same volume of saline injections at days 6 to 7 postoperatively. Scars were assessed independently using the Vancouver Scar Scale, the visual analogue scale, and patient satisfaction rating at the 1-, 3-, and 6-month follow-ups. RESULTS: Overall, 30 patients completed this trial. The botulinum toxin type A-treated side achieved significantly improved Vancouver Scar Scale scores. The most obvious improvements were observed at the 3-month follow-up visit. Among the four subscores of the Vancouver Scar Scale, the most significantly improved subscores were the height and pliability. The visual analogue scale scores also decreased significantly on the botulinum toxin type A-treated side at all three follow-up visits. Approximately 86.7 percent of the patients were satisfied with the scar and epicanthoplasty outcomes. No severe complications were reported. CONCLUSIONS: Early postoperative botulinum toxin type A injection in the medial canthal region efficiently reduces hypertrophic scarring and improves the outcome of epicanthoplasty. Therefore, botulinum toxin type A injection can be used as a routine method to prevent hypertrophic scarring and improve the outcome of epicanthoplasty. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, II.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".