Efficacy and safety of erythritol air‐polishing in implant dentistry: A systematic review
Bibliographic record
Abstract
OBJECTIVES: Professional oral hygiene is essential to prevent peri-implant disease. Appropriate instruments should be employed for implant-supported restorations: they should effectively remove deposits without damaging dental implant surface. The aim of the present systematic review is to investigate the efficacy and safety of erythritol air-polishing in implant-supported rehabilitations, compared to alternative hygienic techniques. MATERIALS AND METHODS: The guidelines reported in the indications of the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) were employed for this systematic review. The focused question was: 'what is the effect of erythritol air-polishing on dental implant surfaces regarding its cleansing efficacy and/or safety?' The final online search was conducted on 13 August 2023; MEDLINE-PubMed, Scopus and Cochrane Library were employed. Comparative in vitro or in vivo original studies were included. RESULTS: The initial database search yielded 128 entries; the final selection comprised 15 articles. The risk of bias was evaluated using the Newcastle Ottawa scale (NOS), the Cochrane Handbook for Systematic Reviews of Interventions, GRADE method. Ultrasonic scaling with PEEK tips, glycine air-polishing and cold atmospheric plasma were the devices most frequently compared to erythritol powder in the included studies. Erythritol air-polishing appeared to be significantly more effective in reducing biofilm compared to other treatments, without causing any significant damage to the implant surface and peri-implant tissues, promoting a good biological response. CONCLUSION: Erythritol air-polishing showed promising results for professional oral hygiene in implant-supported restorations. According to this systematic review, it is effective and safe for removing biofilm from titanium dental implants.
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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 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.012 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| 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".