Using a Zipper Device to Minimize Scarring After Excision of Facial Nevi in Pediatric Patients
Bibliographic record
Abstract
BACKGROUND: This study aims to investigate the safety and effectiveness of using a zipper device to minimize scarring after facial nevi excision in pediatric patients. METHODS: A total of 48 patients were included, with 23 in the control group and 25 in the zipper group. The zipper device was used immediately to equalize skin tension after facial nevi excision. The primary outcome was the scar width measured at 1, 3, 6, and 12 months postoperatively. The Vancouver Scar Scale (VSS) was used to assess patients' scars at postoperative 12 months as a secondary outcome. RESULTS: Two patients in the zipper group withdrew from the trial due to skin irritation. The symptom disappeared within a week after the zipper device was removed. The scar width in the zipper group was smaller than that in the control group at postoperative 1, 3, 6, and 12 months. In addition, the VSS scores for scarring also showed that patients in the zipper group had significantly better scar scores than those in the control group. At postoperative 6 months, scar morphology was essentially similar to that at post 12 months in both groups, and there was a significant positive correlation between scar morphology at the 2 time points. CONCLUSION: It is safe and effective to use this zipper device to minimize scarring after excision of facial nevi in pediatric patients, and we think it be a complementary therapeutic measure in pediatric patients after facial nevus excision. LEVEL OF EVIDENCE: II.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".