Botulinum toxin versus mesotherapy on enhancement of facial scarring (A Controlled Randomized Clinical Trial)
Bibliographic record
Abstract
Background: Most of the body’s tissues can undergo wound repair following a disruption of tissue integrity. Upon healing, these wounds result in scar formation. Botulinum Toxin A (BTA) is known to prevent fibroblast proliferation and it also induces temporary muscle paralysis. Also, mesotherapy is the non-invasive transdermal injection which can aid the skin to increase collagen and elastin production. Thus, both techniques are eligible for enhancement of facial scars.Aim of this study: The study was proposed to compare between the efficacy of early postoperative Botulinum Toxin type A (BTA) injection and mesotherapy growth factor AQ recovery serum on the scar appearance.Materials and methods: Thirty-three patients requiring treatment of facial scars by primary closure were selected for this study and were randomly distributed into three groups. Group A(n=11) received BTA injection while group B (n=11): received mesotherapy growth factor serum with a derma pen injection. Both groups received the injections within a period of 5 days after primary closure. Group C (n=11) the control group where no further treatment was given after primary closure. Follow-up of the patients was at 1, 3 and 6 months postoperatively to evaluate the wound scar enhancement using Vancouver scar scale (VSS) Scores and wound width, in addition to clinical photographs. Results: Results were statistically analyzed and compared using the IBM Statistical Package for Social Science (SPSS) software version 22.0.Conclusion: It can be concluded from this research that both BTA injection and mesotherapy using the micro-needling technique, offered exquisite outcomes on facial scars
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".