Efficacy and safety of thermomechanical fractional injury‐assisted corticosteroid delivery versus intralesional corticosteroid injection for the treatment of hypertrophic scars: A randomized split‐scar trial
Bibliographic record
Abstract
BACKGROUND: Disruption of the natural skin barrier in a controlled manner may be used to deliver drugs that enhance scar resolution. OBJECTIVE: To compare the efficacy and safety of thermomechanical fractional injury (TMFI)-assisted topical corticosteroid delivery with corticosteroid injection in the treatment of hypertrophic scar (HTS). MATERIALS AND METHODS: This was a randomized, split-scar, double-blinded study. Twenty-one subjects with HTS on the abdomen received five split-scar treatments of TMFI + Steroid and steroid injection alone. Changes in scar thickness, scar volume, and Vancouver Scar Scale (VSS) were analyzed. Patient self-assessment, VAS scores, and adverse effects were also evaluated. RESULTS: Scar thickness, volume, and VSS scores of both segments improved significantly compared to baseline. On every follow-up visit, there were no significant differences in mean scar thickness reduction between the two treatment groups except at the 6-month follow-up where the mean scar thickness reduction of the steroid injection segment was significantly lower than that of the TMFI + Steroid segment (95% confidence interval [CI], 0.09-0.35; p = 0.002). Scar volume, VSS scores, and patient self-assessment also showed no significant differences between both segments on all visits. The steroid injection segment was significantly more painful than the TMFI + Steroid segment (95% CI, -2.16 to -1.29; p < 0.001). Adverse effects of skin atrophy, telangiectasia, and post-inflammatory hyperpigmentation were noted in the steroid injection segment, while no adverse effects were observed at the TMFI + Steroid segment. CONCLUSIONS: TMFI-assisted topical corticosteroid delivery is an effective treatment for HTS with a lower risk of adverse effects compared with corticosteroid injection.
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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 | 0.002 |
| 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) | 0.004 | 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".