Prevalence of desquamative gingivitis in patients with oral lichen planus
Bibliographic record
Abstract
Introduction: Given the stress-related nature of desquamative gingivitis (DG), knowing its clinical and epidemiological aspects becomes essential during the COVID-19 pandemic. Therefore, the aim of the present study was to assess the prevalence of DG in patients with oral lichen planus (OLP). Material and methods: All cases displaying clinical and histopathological diagnoses of OLP, treated at our institution from 2000 to 2019 and presenting DG lesions at the time of initial examination were included in the study. Epidemiological, clinical and treatment data were analyzed, including OLP classification. Results: The results showed that 23.3% of the cases presented DG at the time of diagnosis, all were women, with a mean of 46 years old, and diagnosed with erosive OLP. Most were White; the most frequent occupations were homemaker and general services assistant. Half of the included patients presented lesions both in marginal and/or inserted gingiva in the anterior and posterior regions, and the majority (71.4%) related pain or discomfort or burning sensation. Topical triamcinolone acetonide aqueous solution ranging from 0.1%, 0.2% and 0.3% was prescribed for all patients, showing lesion recurrence in 21.4% of them. Conclusion: DG affected women with an average age of 46 years. Triamcinolone acetonide was the drug of choice for the treatment of DG; however, the recurrence rate was high. Therefore, the findings of this study highlight the need for further studies to elucidate the DG behavior and the lesion response to different therapies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".