Keloid Management: A Retrospective Case Review on a New Approach Using Surgical Excision, Platelet-Rich Plasma, and In-office Superficial Photon X-ray Radiation Therapy
Bibliographic record
Abstract
OBJECTIVE: The objective of this retrospective study was to evaluate the efficacy of the authors' combination therapy protocol for keloid treatment. DESIGN: Retrospective. SETTING: Plastic surgery office-based outpatient setting in New York City. PATIENTS: Forty patients with 44 keloid scars requiring surgical excision. INTERVENTIONS: Keloid scars were treated using surgical excision, platelet-rich plasma, and postoperative in-office superficial photon X-ray radiation therapy. Intralesional triamcinolone injections were administered once to 4 patients with poor results on scar scale assessment. Patient follow-up visits ranged from 3 to 11 months to assess for evidence of recurrence and adverse effects. MAIN OUTCOME MEASURE(S): For the purpose of this study, recurrence was defined as any sign of extraordinary erythema, induration, and hypertrophy beyond the site of excision. MAIN RESULTS: In the 16 keloids treated with 2 fractions, there was no evidence of recurrence. One of 25 keloids treated with 3 fractions demonstrated evidence of recurrence. One of 3 keloids treated with a single fraction displayed signs of recurrence. Postirradiation hyperpigmentation was noted in all patients. CONCLUSIONS: Surgical excision combined with platelet-rich plasma and postoperative in-office superficial radiation therapy achieved a 95.5% nonrecurrence rate at 1- to 3-month follow-up. This protocol appears to be a safe and viable option in the management of keloids and merits further randomized controlled study of its comparative efficacy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".