Effect of the combination of photobiomodulation therapy and the intralesional administration of corticoid in the preoperative and postoperative periods of keloid surgery: A randomized, controlled, double-blind trial protocol study
Bibliographic record
Abstract
Keloid scars are characterized by the excessive proliferation of fibroblasts and an imbalance between the production and degradation of collagen, leading to its buildup in the dermis. There is no "gold standard" treatment for this condition, and the recurrence is frequent after surgical procedures removal. In vitro studies have demonstrated that photobiomodulation (PBM) using the blue wavelength reduces the proliferation speed and the number of fibroblasts as well as the expression of TGF-β. There are no protocols studied and established for the treatment of keloids with blue LED. Therefore, the purpose of this study is to determine the effects of the combination of PBM with blue light and the intralesional administration of the corticoid triamcinolone hexacetonide on the quality of the remaining scar by Vancouver Scar Scale in the postoperative period of keloid surgery. A randomized, controlled, double-blind, clinical trial will be conducted involving two groups: 1) Sham (n = 29): intralesional administration of corticoid (IAC) and sham PBM in the preoperative and postoperative periods of keloid removal surgery; and 2) active PBM combined with IAC (n = 29) in the preoperative and postoperative periods of keloid removal surgery. Transcutaneous PBM will be performed on the keloid region in the preoperative period and on the remaining scar in the postoperative period using blue LED (470 nm, 400 mW, 4J per point on 10 linear points). The patients will answer two questionnaires: one for the assessment of quality of life (Qualifibro-UNIFESP) and one for the assessment of satisfaction with the scar (PSAQ). The team of five plastic surgeons will answer the Vancouver Scar Scale (VSS). All questionnaires will be administered one, three, six, and twelve months postoperatively. The keloids will be molded in silicone prior to the onset of treatment and prior to excision to assess pre-treatment and post-treatment size. The same will be performed for the remaining scar at one, three, six, and twelve months postoperatively. The removed keloid will be submitted to histopathological analysis for the determination of the quantity of fibroblasts, the organization and distribution of collagen (picrosirius staining), and the genic expression of TGF-β (qPCR). All data will be submitted to statistical analysis. Trial registration: This study is registered in ClinicalTrials.gov (ID: NCT04824612).
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".