Assessment of Treatment Modalities in Patients With Keloids: A Vancouver Scale Comparison
Bibliographic record
Abstract
Background: Various treatment modalities are used to treat keloids.However, a comprehensive assessment comparing the effectiveness of these modalities in terms of patient-reported outcomes is warranted.Objective: To assess and compare the effectiveness of various treatment modalities for keloids.Methods: We assessed treatment outcomes in a cohort of 250 patients diagnosed with keloids.The patients were categorized into four treatment groups: triamcinolone acetonide (TA), TA + cryotherapy, TA + pulsed dye laser (PDL), and TA + cryotherapy + PDL.The Vancouver Scar Scale was used to evaluate the keloid severity before and after treatment.Results: Significant differences were noted in the Vancouver Scale scores among the treatment groups (p=0.023).Notably, the TA + cryotherapy + PDL group exhibited the most substantial improvement in the Vancouver Scale scores, whereas the TA + PDL group showed the least difference.Pliability was the most significantly improved in the TA + cryotherapy + PDL group (p=0.039).Male patients experienced a greater reduction in pigmentation scores than female patients (p=0.037).Conclusion: Our findings highlight the effectiveness of combined therapies, particularly TA + cryotherapy + PDL, in improving keloid-related parameters.These results offer valuable insights for clinicians in tailoring keloid treatment strategies and support the implementation of combination therapies for enhanced outcomes.This study underscores the importance of comprehensively assessing treatment modalities for keloid management.Combination therapies such as TA + cryotherapy + PDL irradiation have demonstrated significant promise in improving keloid characteristics.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".