Comparision of efficacy of local administration of contractubex & corticosteroids for hypertrophic scar in maxillofacial region
Bibliographic record
Abstract
Abstract Hypertrophic scarring following surgical procedures & trauma are a great concern for patients and a challenging problem for clinicians. The therapeutic management of hypertrophic scars is a problem that has not yet been satisfactorily solved. Contractubex® ointment and intra lesional injection of corticosteroids have been used effectively for treatment and prevention of hypertrophic scars. However very few data is available to determine the efficacy of Contractubex® ointment and intra lesional injection of corticosteroids for the treatment of hypertrophic scar. Two study groups were made with 10 patients in each group. Patients in Group 1 treated with Contractubex® and patients in Group 2 treated with intra lesional corticosteroid (Triamcinolone acetonide). Scar was analyzed with Vancouver Scar Scale (VSS) at 2 weeks, 6 weeks and 12 weeks. The collected data was statistically analyzed. We found that the difference between before and after treatment scores for each of the groups was statistically significant (p < 0.05). The mean of the before and after treatment difference for the Group 1 (Contractubex® ) was 4.7 while that of group 2 (Corticosteroids) was 2.8. This demonstrated a significant superiority of the Contractubex® treatment compared to corticosteroid treatment. The difference between treatment responses for both the groups was statistically significant (p < 0.05). Excellent to good responses were reported in 90% of the Group 1 (Contractubex®) patients and 30% of Group 2 (Corticosteroids).
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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 | 0.001 |
| 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) | 0.002 | 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".