One-Stage Full Mouth Instrumentation (OSFMI): Clinical Outcomes of an Innovative Protocol for the Treatment of Severe Periodontitis.
Bibliographic record
Abstract
AIMS: This case series study aimed to assess the clinical outcomes of a novel protocol for the treatment of patients with severe periodontitis. MATERIALS AND METHODS: Twenty (20) patients with severe periodontitis underwent a single session of One-Stage Full-Mouth Instrumentation (OSFMI) involving supra- and sub-gingival air-polishing with erythritol and chlorhexidine powder and ultrasonic root surface debridement and calculus removal, in association with systemic amoxicillin and metronidazole. Pocket Probing Depth (PPD), Clinical Attachment Level (CAL), Recession (REC), Bleeding on Probing (BOP) and Plaque Index (PI) were collected at baseline (T0), 6 weeks (T1), 3 months (T2) and 6 months (T3). RESULTS: At 6 months, 30% of subjects reached the primary clinical endpoint (less than or equal to4 sites with PD greater than or equal to 5 mm). The percentage of BOP decreased from 49.08 (CI95% 36.06; 62.1) at T0 to 12.97 (CI95% 7.57; 18.37) at T3. The mean number pockets with PPD≥ 5 mm and PPD greater than or equal to 7 mm decreased significantly, from 46.0 and 20.6 at T0 to 11.5 and 2.8 at T3 respectively (p less than 0.001). CONCLUSION: The OSFMI protocol led to clinical results comparable to those obtained with traditional SRP. Researchers are encouraged to test this protocol in randomized clinical trials with longer periods of observation.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".