Clinical Study of Recombinant Human Basic Fibroblast Growth Factor Combined With Collagen Sponge in the Treatment of Maxillofacial Degree II Acute Skin Contusion
Bibliographic record
Abstract
OBJECTIVE: To evaluate the clinical efficacy of recombinant human basic fibroblast growth factor (Rh-bFGF) combined with collagen sponge in the treatment of grade II acute maxillofacial abrasions. METHODS: During the study period from September 2020 to September 2023, 128 such patients were in the authors' hospital and randomly divided into control group (N = 64) and experimental group (N = 64). The observation group was treated with Rh-bFGF and collagen sponge after debridement, while the control group was treated with vaseline gauze after debridement. The healing rate and healing time were observed, and the levels of TNF-α, IL-6, IL-10, EGF, VEGF, and Timp-1 were determined. The Vancouver Scar Scale (VSS) was used to evaluate the local scar hyperplasia 6 months after wound healing in both groups. RESULTS: On the seventh and 14th day of treatment, the wound healing rate in the observation group was significantly higher than that in the control group ( P < 0.05), and the wound healing time in the observation group was lower than that in the control group ( P < 0.05), the levels of TNF-α, IL-6, EGF, VEGF, and Timp-1 in the observation group were lower than those in the control group ( P < 0.05), the levels of Il-10 were higher than those in the control group ( P < 0.05), and the levels of EGF, VEGF, and Timp-1 were higher than those in the control group ( P < 0.05). Vancouver Scar Scale score of local scar hyperplasia was significantly lower than that of control group ( P < 0.05). CONCLUSIONS: Recombinant human basic fibroblast growth factor (Rh-bFGF) combined with collagen sponge in the treatment of maxillofacial contusion can decrease the levels of TNF-α and IL-6, increase the levels of IL-10 and effectively control inflammation, at the same time, it can increase the levels of EGF, VEGF, and Timp-1, promote wound healing and reduce scar hyperplasia. The therapeutic scheme is simple, safe, and effective, and suitable for clinical popularization and application.
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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) | 0.001 | 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 | 0.000 |
| 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".