Microneedling Outcomes in Early Postsurgical Scars
Bibliographic record
Abstract
BACKGROUND: Scars are a vexing sequela of surgery. Microneedling, also known as minimally invasive percutaneous collagen induction, has demonstrated impressive improvements in chronic acne scars; however, no evidence exists for treating postsurgical scars during active wound healing. The purpose of this study was to demonstrate the utility and safe use of minimally invasive percutaneous collagen induction in acute postsurgical scars. METHODS: Twenty-five patients who underwent surgery had scars treated with three treatments of minimally invasive percutaneous collagen induction in the postoperative period. Scar assessment was measured by Vancouver Scar Scale, Patient and Observer Scar Assessment Scale, and Global Aesthetic Improvement Scale after each of the three treatments and at final 2-month follow-up. RESULTS: Patients had positive improvement in Vancouver Scar Scale, Patient and Observer Scar Assessment Scale, and Global Aesthetic Improvement Scale scores at 16-week posttreatment initiation evaluation compared to initial measurement ( p < 0.001). No statistically significant differences were noted when comparing the age of the patient, location of scars, or Fitzpatrick phototype scales among patients. When comparing patients who began treatment early (6 to 7 weeks postoperatively) to those who began treatment late (13 to 16 weeks postoperatively), there was a statistically significant difference in the Patient and Observer Scar Assessment Scale group ( p < 0.04). CONCLUSIONS: Postsurgical scars treated with minimally invasive percutaneous collagen induction in the maturation and remodeling phase had no adverse outcomes. Interestingly, the data show treatment initiated early in the maturation phase (6 to 7 weeks postoperatively), while natural collagen formation was tapering off, demonstrated improved aesthetic outcomes compared to treatments initiated late in the maturation phase (13 to 16 weeks postoperatively). CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, IV.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".