Microneedle-Assisted Steroid Delivery Therapy in the Management of Hypertrophic Scars
Bibliographic record
Abstract
Introduction: Microneedle assisted transdermal delivery is an emerging technique of drug delivery on the horizon with exciting potential therapeutic applications. Aims and Objectives: To study the role of microneedling assisted steroid therapy in the management of hypertrophic scars and make suitable recommendations on employability of the procedure as a treatment modality. Materials and Methods: Twenty six consecutive patients with hypertrophic burn scars were studied. Each scar was divided into two halves–control and test. Both halves received topical fluticasone propionate cream 0.05% once daily, silicone gel sheet and a pressure garment. In addition, the test half received microneedling therapy followed by fluticasone propionate cream 0.05% application twice weekly for twelve sittings. The two halves were evaluated for response using the Vancouver Scar Scale (VSS) at the beginning and end of therapy. Results: Twenty patients completed the study. No statistically significant difference was noted in the VSS scores of the two halves. Subjective relief of pruritus was found to be statistically significant in the test half. Conclusion: This study found that percutaneous microneedling assisted steroid therapy as per the the regimen used in this study produced no objectively assessed benefit in the management of hypertrophic scars. Relief of pruritus was noted.
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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 | 0.000 |
| 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) | 0.001 | 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 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".