Supplementary Material for: The Efficacy and Safety of Botulinum Toxin Type A Injections in Improving Facial Scars: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Botulinum toxin type A (BTA) has a wide range of clinical applications, and its use in improving aesthetics is one of them. The aim of this study was to better assess the efficacy and safety of BTA in patients with facial scars. Summary: We extracted the data of the visual analog scale (VAS) score, Vancouver scar scale (VSS) score, scar width, observer scar assessment scale (OSAS), patient scar assessment scale (PSAS), and/or drug-related adverse events. Five studies provided the data of VAS score, and the results showed that the VAS score in the BTA group was significantly higher than that in the control group. Three randomized controlled trials (RCTs) reported the VSS score. A statistically significant difference exists between the BTA group and the control group. Three RCTs reported the scar width after BTA treatment. A more favorable change was found in the BTA group with scar width even without statistical significance. Data about the OSAS and PSAS scores were available in two trials. There was no significant difference in OSAS and PSAS scores between the BTA group and the control group. Only three studies recorded three slight adverse events. There were no reports of severe complications. In conclusions, this study demonstrated that BTA has the potential to improve facial scars with an acceptable safety profile.
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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 | 0.004 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.564 | 0.023 |
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".