Long-term Clinical Performance of Composite Resin or Ceramic Inlays, Onlays, and Overlays: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Clinical Relevance Composite resin or ceramic inlays, onlays, and overlays can achieve high long-term survival and success rates. SUMMARY Objective: This study evaluated the long-term clinical performance and complications of composite resin or ceramic inlays, onlays, and overlays, as well as identified the factors that might influence the clinical outcome of the restorations. Method: A systematic literature search was conducted in the Pubmed, Embase, Cochrane Central Register of Controlled Trials, and Web of Science databases until April 30, 2019, without language restrictions. Randomized clinical trials, clinical retrospective, and prospective cohort studies with a mean follow-up period of five years were included. Two reviewers extracted the study data independently. Newcastle-Ottawa Scale was applied for quality assessment. Meta-analysis was performed by the random-effects model and fixed-effects model. Results: After removal of duplicates, 2818 studies were identified. Finally, 13 observational studies were included in the meta-analysis based on retrospective and prospective cohort studies. The cumulative survival rate and success rate of composite resin inlays, onlays, and overlays were 91% and 84% after five years of follow-up, respectively. The survival rates of ceramic inlays and onlays were 90% at 5 years, 89% at 8 years and 85% at 10 years, while the success rates of ceramic inlays and onlays were 88% at 5 years and 77% at 10 years. Secondary caries and endodontic complications were the predominant failures for composite resin inlays, onlays, and overlays, while restoration fractures and endodontic complications were the main failures for ceramic inlays and onlays. No direct association between parafuntional habits and bruxism and the fractures of restorations was found. Nonvital teeth and multiple-surface restorations tended to increase the risk of failure. Regarding other factors influencing the clinical outcome, no definite conclusion could be drawn due to inconsistent results. Conclusions: The long-term clinical outcomes have been demonstrated to achieve high survival and success rates based on 10-year data for ceramic inlays and onlays, as well as 5-year data for resin inlays, onlays, and overlays.
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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 | 0.015 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.037 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 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".