Botulinum Toxin Type A for Preventing Facial Trauma and Hypertrophic Scars: A Meta‐Analysis and Trial Sequential Analysis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effectiveness and safety of local injection of botulinum toxin type A in preventing hypertrophic scars after facial trauma and surgery using meta-analysis and sequential experimental analysis methods. METHOD: Computer retrieval of randomized controlled trials on the prevention of facial scars with botulinum toxin type A from PubMed, EMbase, the Cochrane Library, CNKI, China Biomedical Literature Service System, Wanfang Database, and VIP Chinese Science and Technology Journal Full text Database up to February 2025. RESULT: Twelve randomized controlled clinical trials were included, with a total of 644 patients; Type A botulinum toxin injection is superior to the control group in improving patient satisfaction [RR = 6.89; 95% CI (3.20, 14.85); p < 0.0001], Vancouver Scale score [RR = -1.40; 95% CI (-2.73, 0.08); p < 0.0001], visual analog score [RR = 1.41; 95% CI (0.26, 2.56); p = 0.02], scar width [RR = -0.14; 95% CI (-0.17, -0.10); p < 0.0001], and the difference is significant; The incidence of adverse events [RR = 0.38; 95% CI (0.18, 0.84); p = 0.02] and recurrence rate [RR = 0.17; 95% CI (0.04, 0.81); p < 0.03] were lower than those in the control group, and no serious adverse reactions occurred; Sensitivity analysis showed that the results were relatively robust, sequential analysis of the experiment showed that the benefits were conclusive, and Begg's and Egger's tests showed no publication bias. CONCLUSION: Type A botulinum toxin injection has a certain therapeutic effect on hypertrophic scars without significant side effects. However, the accuracy and stability of its therapeutic effect still require more high-quality research verification.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".