Photodynamic Therapy in Treatment of Oral Lichen Planus
Bibliographic record
Abstract
Oral lichen planus (OLP) is a relatively common chronic immunologic mucocutaneous disorder. Although there are many presenting treatments, some of them proved its failure. Recently, the use of photodynamic therapy (PDT) has been expanding due to its numerous advantages, as it is safe, convenient, and non-invasive and has toxic effect towards selective tissues. This article provides comprehensive review on OLP, its etiology, clinical features and recent non-pharmacological treatments. We also describe the topical PDT and its mechanisms. Our purpose was to evaluate the efficacy of PDT in treatment of OLP through collecting the data of the related clinical studies. We searched in PubMed website for the clinical studies that were reported from 2000 to 2014 using specific keywords: "photodynamic therapy" and "treatment of oral lichen planus". Inclusion criteria were English publications only were concerned. In the selected studies of photodynamic treatment, adult patients (more than 20 years) were conducted and the OLP lesions were clinically and histologically confirmed. Exclusion criteria were classical and pharmacological treatments of OLP were excluded and also the using of PDT on skin lesions of lichen planus. We established five clinical studies in this review where all of them reported improvement and effectiveness of PDT in treatment of OLP lesions. The main outcome of comparing the related clinical studies is that the photodynamic is considered as a safe, effective and promising treatment modality for OLP.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".