Airflow for initial nonsurgical treatment of peri‐implantitis: A systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Nonsurgical treatment of peri-implantitis may help in reducing microbial load and inflammatory parameters. The potential clinical benefits of using different treatment approaches, in the initial nonsurgical treatment phase, particularly the airflow, are still not clear. The aim of this systematic review and meta-analyses was to evaluate the outcomes of nonsurgical treatment of peri-implantitis using airflow method in terms of changes in periodontal parameters, peri-implant marginal bone level, postoperative pain/discomfort, and patient satisfaction. METHODS: Electronic databases were searched to identify randomized controlled trials (RCTs) that compared airflow with mechanical debridement using ultrasonic/curettes. The risk of bias was assessed using the Cochrane Collaboration's Risk of Bias tool. Data were analyzed using a statistical software program. RESULTS: A total of 316 studies were identified, of which, five RCTs with 288 dental implants in 174 participants were included. Overall meta-analysis showed more reduction in probing pocket depths at 1-3 months (mean difference [MD] -0.23; 95% confidence interval [CI] -0.50-0.05; p = 0.10) and 6 months (MD -0.04; 95% CI -0.34 to 0.27; p = 0.80) in favor of airflow, but the difference was not statistically significant. The use of airflow was associated with significant reduction in bleeding on probing and increase in peri-implant mucosal recession. The differences in plaque score, peri-implant marginal bone level changes, and patient reported outcomes between airflow and mechanical debridement were not statistically significant. CONCLUSIONS: The short-term clinical and radiographic outcomes following nonsurgical treatment of peri-implantitis using airflow or mechanical debridement were comparable. The airflow has short-term positive effects on reducing bleeding on probing. Further evidence from RCTs are still required to substantiate the current findings.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.035 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".