Comparative antiplaque and antigingivitis effectiveness of tea tree oil mouthwash and a cetylpyridinium chloride mouthwash: A randomized controlled crossover study
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to compare the antiplaque and antigingivitis effects of a mouthwash containing tea tree oil (TTO) with a cetylpyridinium chloride (CPC) mouthwash. MATERIALS AND METHODS: This was a randomized 4 × 4, controlled, cross-over, involving 20 healthy volunteers in a 5-day plaque re-growth model. Test mouthwashes were TTO (Tebodont(®)) and a mouthwash containing CPC 0.05% (Aquafresh(®)). A 0.12% chlorhexidine (CHX) mouthwash (Oro-Clense(®)) was used as positive and colored water (placebo [PLB]) as negative controls. Gingival bleeding index (GBI) and plaque index (PI) scores were recorded before and after each test period. Test periods were separated with 2 weeks washout period. RESULTS: All four mouthwashes significantly (P < 0.001) reduced the GBI scores when compared to the baseline GBI scores. There was no significant difference between PLB and active mouthwashes in the GBI scores. CHX and CPC mouthwashes were found more effective in reducing the PI scores than TTO and PLB mouthwashes. There was no significant difference in PI scores of CHX and CPC mouthwashes. CONCLUSION: 0.05% CPC mouthwash can be an alternative to CHX mouthwash since it is alcohol free and found as efficient as CHX in dental plaque reduction with lesser side effects. More studies are needed to test antigingivitis effects of the mouthwashes used in this study, preferably without initial scaling and polishing.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".