Efficacy of preprocedural mouth rinses (Chlorhexidine, essential oil, and hydrogen peroxide) in reducing bacterial aerosols during dental scaling
Bibliographic record
Abstract
AIM: This study aimed to compare the efficacy of mouth rinsing with chlorhexidine, essential oil, and hydrogen peroxide mouthwashes in reducing bacterial infection in aerosols produced during dental scaling. MATERIALS AND METHODS: Eighty subjects were randomly assigned to four groups. Ten minutes before treatment, participants rinsed for 1 min with 10 mL of either chlorhexidine, essential oil, hydrogen peroxide, or water. Blood agar plates were used to collect aerosols during the scaling procedure, with plates placed at the patient's chest, dentist's chest, and assistant's chest. Plates were exposed for 30 min during and after treatment, incubated at 37 °C for 48 h, and the total number of colony-forming units (CFUs) was counted and analyzed using SPSS-24 software. RESULTS: The mean age of participants was 35.01 years, with 57.5% female and 42.5% male. A statistically significant difference was observed in the number of bacterial colonies on the patient's chest plates (882.56 CFUs), dentist's chest (99.84 CFUs), and assistant's chest (48.49 CFUs) (p value < 0.001). Chlorhexidine mouthwash significantly reduced bacterial growth compared to the other groups. CONCLUSION: Rinsing with chlorhexidine mouthwash before dental treatment effectively reduces bacterial contamination in aerosols, thereby lowering the risk of infection for dental personnel and patients. CLINICAL TRIAL NUMBER: Not applicable.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".