Immediate Postoperative Treatment of Keloids with Intraoperative Radiation Therapy Technology: A Pilot Study
Bibliographic record
Abstract
BACKGROUND: The combination of surgery and postoperative radiotherapy allows for the most effective results with keloids. In this trial, surgery and intraoperative radiation therapy (IORT) technology were used-the hypothesis being that the earlier the application of postoperative radiotherapy, the better the wound healing evolution. METHODS: The study included 16 patients with 21 keloids. The keloids were radically excised and repaired with direct suture or local skin flaps. Collimated electron radiotherapy was applied within 45 minutes of surgery. The outcomes were assessed according to the modified Patient and Observer Scar Assessment Scale; the modified Vancouver Scar Scale; and the modified Common Terminology Criteria for Adverse Events v. 4.0 for skin and subcutaneous tissue disorders. RESULTS: Recurrences were observed in one out of 16 patients, and in two out of 21 keloids (9.5%). The modified Patient and Observer Scar Assessment Scale demonstrated a statistically significant improvement in pain, itching, color, stiffness, thickness, and irregularity after the treatment. The modified Patient and Observer Scar Assessment Scale displayed a statistically significant improvement in the scar vascularity, pigmentation, thickness, and pliability after the treatment. The modified Vancouver Scar Scale demonstrated a statistically significant improvement in 90.48% of the scars after the treatment. The modified Common Terminology Criteria for Adverse Events v. 4.0 for skin and subcutaneous tissue disorders demonstrated an improvement in erythema multiforme and skin pain across the whole sample, with a temporary hyperpigmentation in 19% of the scars after the treatment. CONCLUSION: The combination of surgery and collimated electron radiotherapy with IORT technology demonstrated favorable results in 90.5% of the cases.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".