Removal of refractory erosive-atrophic lichen planus by the CO2 laser.
Bibliographic record
Abstract
UNLABELLED: AIM, STUDY AND BACKGROUND: The erosive-atrophic form of Oral lichen Planus (OLP) is often associated with severe pain and burning sensation. This study investigated the efficacy of CO2 laser surgery for management of refractory erosive-atrophic OLP. METHODS: Ten patients with thirteen erosive-atrophic OLP resistant to standard therapy participated in this study. The size and clinical scores of the lesions and the level of pain/discomfort were recorded before treatment. The lesions were then removed with a CO2 laser device (10600 nm, continuous wave, 5 W, slightly defocused). The subjects were evaluated 1 month and 3 months later and the response rate was assessed according to the decrease in pain, sign scores and size of the lesions. RESULTS: There was a significant reduction in pain and lesion size at 1 and 3 months following laser treatment (p<0.05). The sign scores of the lesions were also significantly improved at follow-up periods compared to the pretreatment state (p<0.05). At the end of the follow-up period, 54% of the lesions showed 3 or 4 degrees of improvement in the clinical score and 23% improved 1 or 2 degrees, whereas 23% remained unchanged post-operatively compared to the pretreatment evaluation. CONCLUSION: The present results indicate that the CO2 laser surgery is an effective modality for management of erosive-atrophic OLP and can be considered as a suitable alternative to standard treatment.
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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 | 0.000 | 0.000 |
| 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) | 0.003 | 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".