Intradermal Botulinum Toxin A on Skin Quality and Facial Rejuvenation: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background: Botulinum toxin A (BTxA) has gained popularity as a nonsurgical aesthetic treatment for skin rejuvenation. However, previous studies on intradermal BTxA have shown inconsistent results. This systematic review and meta-analysis with trial sequential analysis aimed to assess the efficacy and safety of intradermal BTxA for facial rejuvenation. Methods: Following PRISMA guidelines, a comprehensive search was conducted in various databases from January 2008 to March 2023. Outcome measures included sebum production, pore size, skin hydration, skin texture, erythema index, facial wrinkles, and facelift. Eligible studies included human-based clinical trials and prospective cohort studies published in English, focusing on healthy populations requiring facial rejuvenation. Two authors independently screened the titles and abstracts, followed by a full-text review to determine study eligibility. Data extraction and quality assessment were performed by two authors using predefined criteria. Results: Ten studies met the inclusion criteria, including five randomized controlled trials and five prospective cohort studies with 153 participants. Studies revealed positive effects of intradermal BTxA on various outcome measures related to facial rejuvenation. These effects included improvements in sebum production, pore size, erythema index, facial wrinkles, skin texture and elasticity, and overall facelift but not skin hydration. All failed to reach the required information size in the trial sequential analysis. Conclusions: Findings suggest positive outcomes in multiple attributes of skin quality and facial rejuvenation. However, more high-quality research is needed to establish definitive conclusions. These findings contribute to the evidence base for nonsurgical aesthetic treatments, emphasizing the importance of ongoing research in this field.
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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 | 0.018 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".