Impact of Vitamin D Injection on Keloids and Hypertrophic Scars
Bibliographic record
Abstract
BACKGROUND: Hypertrophic scars and keloids are human cutaneous fibroproliferative conditions that develop after burns, trauma, surgery, and inflammation. Vitamin D inhibits keloid fibroblast proliferation by reducing TGF-β-induced extracellular matrix formation, boosting matrix metalloproteinase activity, and reducing inflammation. AIM: To study the effect of intralesional and systemic Vitamin D3 injection on hypertrophic scars and keloids and whether vitamin D3 deficiency increases scarring. PATIENTS AND METHODS: This study included 30 hypertrophic scars and keloid patients divided into groups depending on serum vitamin D levels. Every patient was tested for vitamin D using ELISA. Group I: patients with vitamin D deficiency or insufficiency received a systemic injection of vitamin D (cholecalciferol 200 000 I.U.) once monthly for 3 months with a calcium oral supplement and intralesional vitamin D injections on hypertrophic scars and keloids. Group II: patients with sufficient vitamin D received only intralesional vitamin D injections. RESULTS: Vitamin D deficiency did not affect scar formation or severity (total Vancouver scar scale before assessment) with a p value > 0.05. All instances showed a substantial drop in vascularity, pliability, and total Vancouver scale score (p value < 0.05) following intervention, but no change in scar pigmentation or height. Scar assessment following intervention did not significantly differ between research groups (p > 0.05). CONCLUSION: Injection of vitamin on hypertrophic scars and keloids enhances vascularity and pliability in patients with sufficient serum vitamin D levels and those with deficient or insufficient serum vitamin D levels after improving them by systemic injection of vitamin D without any effect on height and pigmentation of scars. TRIAL REGISTRATION: NCT06301178.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".