A Randomized, Double-Blind, Active- and Placebo-Controlled Trial Evaluating a Novel Topical Treatment for Keloid Scars
Bibliographic record
Abstract
Keloid and hypertrophic scars are fibroproliferative disorders resulting from abnormal wound healing in genetically susceptible individuals. Current therapies are often ineffective. Kynurenine shows promise as a topical treatment for keloids and hypertrophic scars. In this study, healthy adult male and female subjects seeking treatment for mature keloid scars were enrolled. Subjects were randomized in double-blind fashion to receive kynurenic acid 0.5% (FS2) cream (Group 1), an active onion extract comparator treatment (Group 2), or the inactive vehicle (Group 3). Each treatment was applied twice-daily. Qualitative assessments were made using the Vancouver Scar Scale (VSS), as well as the Patient and Observer Scar Assessment Scales (POSAS). Among subjects in Group 1, there was a substantial decrease in mean PGSS scores after 30 days of treatment that continued to trend downward, becoming significant versus Group 2 at days 90 and 180 (P<0.05) and versus Group 3 at day 180 (P<0.01). Based on mean VSS scores, subjects in Group 1 achieved beneficial effects that became significant versus Group 2 at day 90 (P<0.01), day 120 (P<0.05), and day 180 (P<0.001) and versus Group 3 at day 180 (P<0.05). There were no significant improvements in Groups 2 or 3. There were no adverse events or local skin reactions. The twice-daily application of FS2 Cream represents a potentially new and effective treatment for mature keloid scars. J Drugs Dermatol. 2021;20(9):964-968. doi:10.36849/JDD.6197.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.009 | 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".