Assessment of intralesional injection of botulinum toxin type A in hypertrophic scars and keloids: Clinical and pathological study
Bibliographic record
Abstract
Keloids and hypertrophic scars are cosmetic problems with significant morbidity. Many clinical modalities were tried in order to modulate the disfigurement related to these pathologic scars. To evaluate the clinical and histopathological effects of Botulinum toxin type A (BTX-A) injection on keloids and hypertrophic scars. Twelve patients with keloids and 8 with hypertrophic scars were enrolled in this study. Botulinum toxin type A was injected intralesional (1 session/month) for three sessions. Clinical outcome was assessed via Vancouver Scar Scale (VSS), Observer Scar Assessment Scale (OSAS), and the Patient Scar Assessment Scale (PSAS). Histologic grading scores were used to assess the changes in the quality of collagen and elastic tissues and image analysis was used to detect their quantitative morphometric changes. This study showed a high statistically significant difference between baseline and the result after each of the three sessions of injection and 3, 6 months after the last session regarding VSS, OSAS, and PSAS with p value ≤0.001 for each. The study also showed that there was a statistically significant difference between the histopathologic findings before injection of BTX and 1 month after the third session regarding all parameters used. Botulinum toxin type A can be a good therapeutic maneuver for management of keloid and hypertrophic scars with significant clinical and histologic improvement.
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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 | 0.001 |
| 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".