Antimicrobial efficacy and bonding properties of orthodontic bonding systems enhanced with silver nanoparticles: a systematic review with meta-analysis
Bibliographic record
Abstract
The aim of this systematic review was to assess the antimicrobial effectiveness of silver nanoparticles (AgNPs) incorporated to different orthodontic bonding systems. Additionally, the review investigated the impact of AgNPs on the bonding properties of these materials. The hypothesis posed that the addition of AgNPs would enhance the antimicrobial efficacy of orthodontic bonding systems while maintaining their bonding properties. The systematic review employed a PICO-based search strategy, targeting in vitro studies focusing on the integration of nano silver particles into orthodontic bonding systems with potential antimicrobial activity. The intervention involved the use of nano silver in orthodontic bonding systems, with a comparison to systems lacking nano silver. The primary outcomes assessed were antimicrobial activity and shear bond strength (SBS). The search process, conducted without publication date restrictions, yielded 551 potential articles: 34 from PubMed, 360 from PubMed Central, 42 from Embase, 54 from Scopus, and 61 from Web of Science. Ultimately, a qualitative synthesis was conducted on 13 papers. The PRISMA diagram, visually represented the search strategy, screening process, and inclusion criteria. The study protocol was registered in PROSPERO CRD42023487656 to enhance transparency and adherence to systematic review guidelines. Quality assessment of the included studies was performed using the Newcastle-Ottawa Scale, revealing that the 13 articles meeting the inclusion criteria demonstrated a high level of evidence. Seven studies were included in the meta-analysis regarding shear bond strength. In summary, the synthesized findings from these studies strongly underscore the promising potential of orthodontic materials modified with AgNPs. These materials exhibit effective resistance against cariogenic bacteria without compromising bonding properties below clinical acceptability. Such innovative materials hold significant implications for advancing oral health within the realm of orthodontics.
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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 | 0.017 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.030 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".