Best oral self-care practices for peri-implant conditions and diseases: a systematic review
Bibliographic record
Abstract
Introduction The increasing prevalence of dental implants has brought greater attention to the prevention and management of peri-implant diseases, which can compromise long-term implant success. This systematic review evaluated the current evidence on oral self-care practices for maintaining peri-implant health in healthy, non-smoking adults. Methods This systematic review was reported in accordance with the PRISMA 2020 statement and registered in the PROSPERO database (CRD420251028140). PICO methods and guidelines for the Center for Evidence-Based Medicine were used to develop the focus question, “ What are the best practices for oral self-care for the prevention and management of peri-implant conditions and diseases?” Risk of bias was determined by applying the ROBIS Tool to assess risk of bias in systematic reviews and the revised Cochrane risk of bias tool for randomized trials (RoB2). Results Across 12 studies, interventions were categorized into five domains: toothbrushes, interdental aids, toothpaste, mouth rinses/topicals, and multi-modal self-care strategies. Powered toothbrushes, particularly oscillating-rotating models, demonstrated superior plaque and inflammation reduction compared to manual options. Triclosan-containing toothpastes consistently outperformed fluoride-only formulations in decreasing plaque, bleeding on probing, and pathogenic bacteria. Interdental aids such as interproximal brushes and oral irrigators were more effective than floss in reducing inflammatory markers. Stannous fluoride-based rinses showed potential anti-inflammatory benefits, while prolonged chlorhexidine use may elevate inflammatory cytokines. Discussion A multimodal approach combining mechanical and chemical adjuncts was most effective for peri-implant disease prevention. These findings emphasize the importance of individualized, evidence-based home care protocols in preserving implant longevity and reducing peri-implant disease burden. Systematic Review Registration https://www.crd.york.ac.uk/PROSPERO/view/CRD420251028140 , PROSPERO CRD420251028140.
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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 | 0.012 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".