A randomized trial of the effectiveness of an ultrasonic denture hygiene intervention program among communitydwelling elders*
Bibliographic record
Abstract
Purpose: This study aimed to assess the effectiveness of ultrasonic denture hygiene interventions in improving denture cleanliness among elderly individuals. Materials and methods: Sixty-six participants who had received upper metal framework removable partial dentures within the past 5 years were randomly allocated into three denture hygiene intervention groups: group 1 (mechanical cleaning with a toothbrush and ultrasonic cleaning with cetylpyridinium chloride), group 2 (mechanical cleaning with a toothbrush and ultrasonic cleaning with distilled water), and control (mechanical cleaning with a toothbrush only). Denture cleanliness was assessed at baseline and 1-month using: i) Denture Cleanliness Index (DCI) scores; ii) plaque coverage percentage; and (iii) microbiological samples for bacterial and yeast detection. Differences between groups were assessed with one-way analysis of variance and Chi-squared tests. Results: Mean DCI scores and mean percentages of plaque coverage area were significantly reduced in group 1 and group 2, compared to the control group for both cobalt chromium (CoCr) and acrylic fitting surfaces (p<0.001). No significant differences were found between groups 1 and 2 with regard to the prevalence and viable counts of yeasts or total microbial viable counts. No significant differences in the investigated clinical and microbiological parameters were observed between CoCr and acrylic surfaces following the intervention period. Conclusion: The ultrasonic cleaner was significantly more effective than mechanical cleaning in the reduction of biofilm coverage on metal framework removable partial dentures over a 1-month intervention period. Nevertheless, the adjunctive use of cetylpyridinium chloride with ultrasonic cleaning did not yield additional benefits.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".