Assessing keloid recurrence following surgical excision and radiation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Keloids are a fibroproliferative disorder that can result from a cutaneous injury to the reticular dermis. Recurrence rates as high as 100% have been reported following surgical excision alone. Consequently, a variety of post-surgical techniques have been employed to prevent keloid recurrence, including the use of radiation. Although numerous studies have shown post-excisional X-rays, electron beam, lasers and brachytherapy can reduce the rate of keloid recurrence, numerous inconsistencies, including a wide range of definitions for keloid recurrence, make it difficult to compare study outcomes. The review aims to examine the various means for defining keloid recurrence in clinical trials involving the use of radiation therapy. Searches of the Cochrane Library and PubMed were performed to identify the available information for post-surgical keloid recurrence following radiation therapy. Each identified study was reviewed for patient follow-up and criteria used to define keloid recurrence. The search results included clinical studies with external beam radiation, brachytherapy and superficial radiation therapy. Many studies did not include a definition of keloid recurrence, or defined recurrence only as the return of scar tissue. Other studies defined keloid recurrence based on patient self-assessment questionnaires, symptoms and scar elevation and changes in Kyoto Scar Scale, Japan Scar Workshop Scale and Vancouver Scar Scale scores. The results of this review indicate keloidectomy followed by radiation therapy provide satisfactory recurrence rates; however, clinical studies evaluating these treatments do not describe treatment outcomes or use different definitions of keloid recurrence. Consequently, recurrence rates vary widely, making comparisons across studies difficult. Keloid recurrence should be clearly defined using both objective and subjective measures.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it