Ultrapulse Fractional CO2 Laser With Different Fluences and Densities in the Prevention of Periorbital Laceration Scars: A Split-Scar, Evaluator-Blinded Study
Bibliographic record
Abstract
BACKGROUND: Periorbital laceration can result in complex, permanent scars, and even lead to serious complications such as cicatricial ectropion. Early intervention with laser devices has been suggested as a novel modality to reduce scar formation. However, no consensus exists regarding the optimal treatment parameters for scar management. This study evaluated the efficacy and safety of ultrapulse fractional CO 2 laser (UFCL) with different fluences and densities in preventing periorbital surgical scars. OBJECTIVE: To assess the efficacy and safety of UFCL with different fluences and densities in the prevention of periorbital laceration scars. METHODS: A prospective, randomized, blinded study was conducted on 90 patients with periorbital laceration scars of 2 weeks old. Four treatment sessions of UFCL were administered to each half of the scar at 4-week intervals, with halves treated with high fluences with low density versus low fluences with low-density treatment. Vancouver Scar Scale was used to assess the 2 portions of each individual scar at baseline, final treatment, and 6 months. The patient's 4-point satisfaction scale was used to evaluate the patient's satisfaction at baseline and 6 months. Safety was evaluated by registration of adverse events. RESULTS: Eighty-two of 90 patients completed the clinical trial and follow-up. There was no significant difference in Vancouver Scar Scale and satisfaction score between different laser settings between the two groups ( P > 0.05). Adverse events were minor and no long-term side effects were noted. CONCLUSIONS: Early application of UFCL is a safe, strategy to significantly improve the final traumatic periorbital scar appearance. Objective evaluation of scars did not identify differences in scar appearance between high fluences with low density versus low fluences with low density of UFCL treatment. LEVEL OF EVIDENCE: Level III.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".