[Clinical study on the relationship among the dermis, fat dome and postburn hyperplastic scar formation].
Bibliographic record
Abstract
OBJECTIVE: To explore the influence of dermal defect and fat dome structure destruction in burn wounds on the formation of hyperplastic scar. METHODS: Fifty two wounds in 24 burn patients with deep partial thickness burn indicating tangential excision in the extremities were enrolled in the study, and they were divided into three groups according to the extent of exposure of dermal fat granules, i.e. A (without fat exposure), B (with little fat exposure) and C (with much fat exposure) groups. These three groups were subdivided into A1 (without grafting), A2 (grafting with razor thin skin), B1 (without grafting), B2 (with razor thin skin grafting), C1 (without grafting) and C2 (with split-thickness skin grafting) groups, with 9 wounds in each group. The dermal depth and exposure rate of the fat granules in each group were measured and analyzed by KS400 photography analysis apparatus. The follow-up conditions of the scars 6 months after operation were evaluated with Vancouver remark system by Vancouver score assessment. RESULTS: There was obvious difference in the dermal depth and exposure rate of the fat granules among all the groups (P < 0.05 or 0.01). The fat exposure rate was positively correlated with the extent of the dermal defect (gamma = 0.554, P < 0.05). The Vancouver score in group A was lower than that in B and C groups (P < 0.05), while that in B1 group (3.714 +/- 2.498) was evidently higher than that in other groups (P < 0.01). The scar score was lowered when the wounds were grafted with the dermis with its thickness similar to the depth of the defect, The scar score was increased along with the elevation of fat exposure rate (P < 0.05). CONCLUSION: There was a positive correlation between the degree of dermal defect and that of hyperplastic scar after burns. The disruption of fat dome structure might also be an important factor in the scar development.
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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) | 0.004 | 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".