Comparison between Dermoscopic and Histopathological Features of Keloids and Hypertrophic Scars Before and After Different Treatment Modalities.
Bibliographic record
Abstract
Background: Keloids and hypertrophic scars (HTS) are abnormal wound responses. Lack of knowledge about their basic biology had prevented development of a targeted approach to the treatment of keloids and hypertrophic scars.Aim of the work: The study aimed to evaluate the dermoscopic and histopathological features of keloids and hypertrophic scars before and after different treatment modalities. Methods: Thirty-two patients with keloids and hypertrophic scars were included in the study for clinical, dermoscopic and histopathological examination.patients receieved tratment in form of Fractional Co2 laser or 5FU or verapamil . Examination of slides stained by H&E and the special stain (Masson trichrome) was performed, also CD31 immunohistochemistry was performed in all cases. The histopathological examination of slides both HTS and keloid before and after treatment was done. The pattern of collagen fibers was determined by hematoxylin and eosin stained sections and Masson Trichrome stained sections. The pattern and extent of vascularity demonstrated by CD31 immunostaining was evaluated.Results: Vancouver scar scale showed significant improvement in all patients. histopathological improvement (the collagen fibers detected by Masson trichrome in the upper dermis of HTS cases become thinner and the MVD detected by CD31 IHC staining showed increased vascularity after treatment). Hypertrophic scars showed better improvement than keloids in all groups. Arborizing and linear vessels showed significant improvement in group 1&2. Linear vessels showed significant improvement in group 3. Conclusion: Fractional Co2 laser combined with 5FU is an excellent choice of treatment in keloids and hypertrophic scars.
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 | 0.000 | 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) | 0.001 | 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".