Clinical observation of the long-term effects of rhEGF on deep partial-thickness burn wounds
Bibliographic record
Abstract
Objective To evaluate the safety and long-term effect of recombinant human epithelial growth factor (rhEGF) on deep partial-thickness burn wounds. Methods Thirty-seven burn patients were enrolled in this study and were observed by randomized, double-blinded and placebo-controlled protocol. An area of deep partial-thickness burn wounds from each patient was divided into control (C) and treatment (T) portions. The wound in C was treated with normal saline while that in T with rhEGF. The patients were followed-up for 1 and 4 years after wound healing. The healed wounds were evaluated by modified Vancouver scar scale in terms of scar index (SI). Results 1 year after wound healing, it was found that the SI in T group (7.19±1.67) was obviously lower than that in C group(8.92±1.78, P 0.01). The SI in T group (6.12±1.54) was still evidently lower than that in C group(8.09±1.81, P 0.01) four years after wound healing. There were no signs of development of tumor or cancer in all the tested burn wound areas. Conclusion External application of rhEGF might be beneficial to the healing quality of deep partial-thickness burn wound with less scar formation and better long-term effects, and it is safe.
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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".