CLINICAL EVALUATION OF MESOTHERAPY ON THE IMPROVEMENT OF FACIAL SCARS (RANDOMIZED CONTROLLED CLINICAL TRIAL)
Bibliographic record
Abstract
INTRODUCTION: If a tissue's integrity has been compromised, most body tissues can go through wound healing and leave behind scars when they recover. Mesotherapy is a non-invasive transdermal injection into the skin which stimulating fibroblasts for collagen and elastin biosynthesis and facilitating cell-to-cell communication that can be used to heal face scars. Objective: To improve the profile appearance and assessment the effectiveness of mesotherapy (microneedling) on the improvement of early postoperative oblique or vertical face surgical scars. Materials and Methods: Twenty-four patients with oblique or vertical forehead lacerations who underwent primary closure within five days. Randomly divided into two groups: Group 1 (n=12) was given mesotherapy (microneedling) and group 2 (n=12) was given no further treatment. At the 1, 3, and 6-month follow-up appointments, the Vancouver scar scale (VSS) scores and wound diameter will be assessed, along with clinical pictures and an assessment of the scar's pigmentation. Results: At the 1-month follow-up, both groups had significantly improved. After 3 months, follow-up, the mesotherapy (microneedling) group displayed more significant changes in VSS, wound breadth, and color difference scores than the control group. Patients from both groups relapsed to their original records during the follow-up at 6 months. Conclusion: Significant progress was achieved in the VSS and in the wound width with Mesotherapy (microneedling) group compared to the control group. All the major changes were observed in the 3 and 6-month visits.
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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) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 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".