Efficacy of Qingshuanglu Exposure Combined with Oral Administration of Diosmin for Burn Scar Improvement and its Effect on Serum Levels of Pro-Inflammatory Factors
Bibliographic record
Abstract
To analyze the efficacy of Qingshuanglu in improving burn scars. First, 120 burn individuals were recruited and all the participants were given oral administration of diosmin and then randomized to Meibao Shi Run Shao Shang Gao and Qingshuanglu. Efficacy, visual analogue scale, vancouver scar scale score, pigmentation rate, wound drying time, healing time, safety, and serum inflammatory factor levels were comparatively analyzed. Patients receiving Qingshuanglu treatment showed shorter wound drying and healing time, lower visual analogue score, vancouver scar score, reduced pigmentation rate and total incidence of adverse reactions than those treated with Meibao. Moreover, markedly decreased levels of various serum inflammatory factors were observed in patients receiving Qingshuanglu, lower than the pre-treatment levels and those receiving Meibao. The study demonstrates that Qingshuanglu exposure could effectively repair burn injury, attenuate the inflammatory response, and reduce the scar formation for burn patients.
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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 | 0.000 |
| 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".