EFFECT OF VITAMIN D DEFICIENCY ON HYPERTROPHIC SCARRING: A meta-analysis.
Bibliographic record
Abstract
Background: : Vitamin D is a fat soluable vitamin which is vital for different systems of the human body including endocrine and immune systems, endothelial function and wound healing.Patients and methods: This meta-analysis follows the PRISMA flow diagram. The study asses the relationship between vitamin D deficiency and hypertrophic scar incidence and determine vitamin D replacement therapy effect on hypertrophic scar width and scale in patients who have deficiency in vitamin D.Result: After the search and screening, one study was eligible for our meta-analysis. Results of meta-analysis shows that scar improvement occurred significantly with p value < 0.05 after vitamin D replacement in group (1) and this was represented by low level of Vancouver score but scar width did not change after treatment in both study groups.Conclusion: Our study may provide evidence that Vitamin D supplement may be used like an adjuvent treatment for hypertrophic scars as it reduce vascularity, pliability, pigmentation, and height of scars with little effect on scar width.Keywords: Vitamin D – hypertrophic scarring.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.030 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".