Effect of Addition of Metal Oxide Nanoparticles on the Strength of Heat-Cured Denture Base Resins: Protocol for Systematic Review and Meta-Analysis of In Vitro Studies
Bibliographic record
Abstract
BACKGROUND: Metal oxide nanoparticle-reinforced polymethyl methacrylate (PMMA) has been shown to improve mechanical properties, such as strength. Different types of metal oxide nanoparticles have been used previously, but the comparative effect on the strength of heat-cured denture base resins remains unclear. OBJECTIVE: This is a protocol for a systematic review and meta-analysis that will aim to pool evidence to compare and analyze the effects of the addition of different metal oxide nanoparticles, with varied sizes and concentrations, on the strength (flexural, impact, transverse, compressive tensile strength, and fracture toughness) of heat-cured PMMA. In addition, this review aims to analyze methodological factors, such as adherence to testing and sample-making guidelines, and the effects of surface treatments of the nanoparticles on the strength of heat-cured denture base resins. METHODS: The protocol has been registered in the Open Science Framework. Search strategies to identify studies on the effect of metal oxide nanoparticles on the strength of heat-cured PMMA were developed by the subject matter expert in library science. Following this, a systematic search of 5 electronic databases (PubMed [NCBI], Scopus [Elsevier], Cochrane Library [Wiley], CINAHL Plus with Full Text [EBSCO], and Dimensions Free Web App) was conducted to retrieve in vitro studies published in English from January 2012 to October 2023. Along with this citation chasing, other online sources and gray literature were also searched. Furthermore, papers will be screened, and appropriate data elements will be extracted in a standardized manner. A risk-of-bias assessment will be performed using a modified Cochrane Risk of Bias Tool. A meta-analysis will be performed using a random-effects model. RESULTS: Search in databases resulted in 1837 papers, of which 1752 were duplicates, leaving 85 records that were screened for titles and abstracts based on the eligibility criteria. A similar search run on other online sources identified 129 papers that will be further analyzed for inclusion. The study was initiated in November 2023 and research questions and search strategies were formulated. The proposed study is expected to be completed by December 2024. CONCLUSIONS: This systematic review will comprehensively analyze the effects of the incorporation of metal oxide nanoparticles in heat-cured denture base resins on the strength of the material. We anticipate gaining a deeper understanding of the effects and method of use of metal oxide nanoparticles to improve the strength of PMMA denture base resins. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/59999.
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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 | 0.066 | 0.103 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.023 | 0.031 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.031 | 0.003 |
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".