Intralesional pentoxifylline, triamcinolone acetonide, and their combination for treatment of keloid scars
Bibliographic record
Abstract
BACKGROUND: Keloids are common fibroproliferative tumors, and their treatment still represents a dilemma. Intralesional triamcinolone acetonide (TAC) injection is effective, but frequently associated with side effects. Pentoxifyllin (PTX) is a vasodilator, anti-inflammatory, and antifibrotic agent. Its intralesional injection in keloids has not been evaluated yet. AIMS: Evaluating the efficacy and safety of intralesional PTX versus intralesional TAC and their combination for treatment of keloids. PATIENTS/METHODS: Thirty patients with keloids were divided into three equal groups and treated by intralesional injection of TAC, PTX, or their combination (admixed in 1:1 ratio). Injections were repeated every 3 weeks until lesional flattening or for maximum of 5 sessions. The evaluation was done using the Vancouver Scar Scale and the Verbal Rating Scale for pain and itching. RESULTS: A significant improvement in VSS was detected in all groups. Significantly better improvements in keloid height, pliability, pain, and itching were detected in the TAC and combination groups than in the PTX group. There was a significantly higher incidence of side effects (atrophy, hypopigmentation, telangiectasia, and precipitation of TAC) in the TAC group than in the combination group, while no side effects were reported in the PTX group. A statistically significant reduction in the number of treatment sessions (required to achieve best results) was detected in patients in the combination group. CONCLUSIONS: Intralesional injection of PTX is a potentially helpful, safe, and well-tolerated therapeutic tool for keloids, but with lower efficacy than intralesional TAC when used solely. Combining PTX and TAC produces significantly better results for keloid treatment and lowers the risk of TAC-induced side effects.
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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".