Palatal brushing for the treatment of denture stomatitis: A multicentre randomized controlled trial
Bibliographic record
Abstract
PURPOSE: To determine the effectiveness of palatal brushing in the treatment of denture-related erythematous stomatitis (DES) in complete denture wearers. METHODS: This two-parallel-arm RCT was conducted in three university clinics in Brazil, Canada, and Chile. Participants (n=77) were randomly allocated to receive (i) instructions for palatal brushing and standard oral/denture hygiene ("intervention"); or (ii) standard oral/denture hygiene instructions only ("control"). Data collection was carried out at the baseline and at 3 and 6 months after intervention. Outcomes included the magnitude of oral Candida carriage and the degree of inflammation of denture-bearing tissues. Groups were compared using generalized estimating equations and chi-square test (α=0.05). RESULTS: Palatal inflammation levels were reduced significantly in the "intervention" compared to "control" group at 6 months (intervention: 70%, control: 40%; chi-square, p=0.04). There was no between-group significant difference in the Candida count from denture and palatal biofilms; however, a subgroup analysis restricted to baseline Candida carriers showed further reduction with the intervention at 6 months. No adversity was observed by trialist or reported by participants. CONCLUSIONS: Including palatal brushing in oral instructions for denture wearers has positive impact on DES-related mucosal inflammation. Thus, our findings endorse the inclusion of palatal brushing in standard oral hygiene instructions to treat DES.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".