A short-term study of the effects of ozone irrigation in an orthodontic population with fixed appliances.
Bibliographic record
Abstract
AIM: The aim of the present study was to compare the clinical efficacy of chlorhexidine and ozonised water in the oral hygiene maintenance of orthodontic patients. MATERIALS AND METHODS: Study design: This is a prospective clinical study. Thirty patients with orthodontic brackets were selected at the Versilia General Hospital (Lido di Camaiore, Italy). Patients were randomly allocated to one of two groups: standard oral hygiene session followed by prescription of either chlorhexidine mouth-rinse or ozonated water. At each moment of the follow-up, the following parameters were recorded: pocket probing depth (PPD), full-mouth plaque index (FMPI), and full mouth bleeding score (FMBS). STATISTICS: Sample size was computed according to previously published data. Significance level was set at 0.05 for all analyses, and non-parametric Wilcoxon signed rank test was used for comparisons. RESULTS: At baseline, mean PPD was 1.89 ± 0.13 mm for the control group and 1.95 ± 0.10 mm for the test group. Mean FMPI was 63.9 ± 16.5% and 68.7 ± 10.33% respectively. Mean FMBS was 31.5 ± 15.6% and 32.8 ± 8.85 respectively. One month after treatment (T2), both groups showed a significant improvement of FMPI and FMBS. Mean FMPI was 42.8 ± 14.3% and 24.3 ± 6.41% respectively. Mean FMBS was 19.5 ±12.6% and 4.70 ± 3.56% respectively. The test group treated with ozone exhibited a greater improvement of FMPI and FMBS. CONCLUSIONS: Ozone yielded better outcomes than chlorhexidine in the management of gingivitis in orthodontic patients. Ozone should be further investigated in longitudinal studies with larger samples.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".