Effect of 0.2% chlorhexidine on microbial and fungal contamination of dental unit waterlines.
Bibliographic record
Abstract
BACKGROUND: It is known that dental unit waterline can be a source of infection. The aim of this study was to evaluate the efficacy of a mouthwash, chlorhexidine, in controlling microbial and fungal contamination of dental unit waterlines. MATERIALS AND METHODS: In the present experimental study, the water in high-speed handpieces and air/water syringes of 35 dental units in a dental school was investigated microbiologically. Five of the units and one tap water served as controls; 100-200-mL water samples were collected aseptically in sterile containers in the morning after a 2-min purge. Water reservoir bottles were emptied and 50 mL of 0.2% chlorhexidine mouthwash was introduced into the tank. Then the water syringe was used to flush the waterline until the pink-colored chlorhexidine was observed to flow from the water syringe. Before the next day's session and before the students used the unit, two water samples from the water syringe and water turbine was collected. The samples were transferred to the laboratory. After 48 h at 37°C, the microbial colonies were counted. The number of these colonies was evaluated using colony forming unit CFU. Data were analyzed with Mann - Whitney U test and SPSS 13.5 statistical program. The statistical significance was defined at P ≤ 0.05. RESULTS: All 35 units were contaminated before chlorhexidine use; no contamination was detected after adding chlorhexidine to the waterlines of the units. After week 1, 28 of the 30 treated dental unit waterlines (DUWLs) had values of CFU/mL less than 200. CONCLUSION: The present study showed that the use of chlorhexidine could reduce microbial counts in dental unit waterlines.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".