Comparison of Therapeutic Response of Keloid to Intralesional Injection of Triamcinolone Acetonide and Bleomycin
Bibliographic record
Abstract
Background: Keloids are an aberration of normal healing process. Majority of the cases are symptomatic and indolent to treat. Though there is no ideal monotherapy, intralesional injection of triamcinolone acetonide is one of the first line treatment. Triamcinolone has a variable sensitivity, chance of complication and recurrence. As an emerging novel treatment, intralesional application of bleomycin shown promise in several studies. Materials and Methods: Single blind comparative study done at Sheikh Hasina National Institute of Burn and Plastic Surgery, Dhaka, Bangladesh from February, 2019 to August, 2020. Purposive sampling of 50 adult patients with keloid were enrolled, later by lottery with sealed envelope were done, to allocate into two groups A and B. They were given intralesional injection of triamcinolone acetonide and bleomycin every four weeks respectively. Both groups were assessed before and followed up every two months for a total of six months after completion of three dose of intralesional infiltration. Outcomes were compared against each other as per Vancouver scar scale score, numeric rating scale score for pain and itching. Results: Majority of the subjects (23) belonged to 18-24 years age group. In group A (triamcinolone acetonide), mean Vancouver scar scale score remission rate was 34.46% and In group B (bleomycin), it was 49.6% over 6 months follow up. Remission rate of pain in group B was 92%, while in group A it was 42%. Remission rate of itching in group B was 77.7% and in group A it was 34.2%. Conclusion: Intralesional injection of bleomycin is better for the treatment of keloid than triamcinolone acetonide.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| 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".