Clinical Longevity of Complex Direct Posterior Resin Composite and Amalgam Restorations: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Objective: The use of resin composites (RC) for complex restorations, including those involving cusp coverage, has increased dramatically in recent years. However, reports in the literature regarding the performance of posterior multisurface RC and amalgam (AM) restorations show conflicting results. This systematic review and meta-analysis aims to assess the clinical performance of complex (involving two or more surfaces) direct posterior resin composite and amalgam restorations in permanent teeth. Methods: Inclusion criteria were for prospective randomized controlled trials (RCTs) of multisurface direct RC and AM restorations of permanent posterior teeth with a follow-up period of three years or more. The trials needed to include a minimum of 20 restored teeth for each evaluated material. Retrospective studies, studies lacking survival rates or clearly reported reasons for failure, and those with unclear randomization methods were excluded. Five bibliographic databases (Medline-OVID, Embase, Cochrane Library, Web of Science, and LILACS [Latin American and Caribbean Health Sciences Literature Database]) and manual searches were screened. The Cochrane Risk of Bias Tool was used to assess the included studies. Random-effects meta-analyses were conducted using the Freeman-Tukey double arcsine transformation and the DerSimonian-Laird random-effects model to evaluate restorative failures and compare the survival of AM and RC restorations. Results: From the 6303 identified studies, 198 underwent meticulous examination, and 15 RCTs met the inclusion criteria. Only two studies compared AM and RC restorations. Although the combined data from these studies showed a trend toward higher failure rates in multisurface RC restorations, the difference was not statistically significant (p=0.06). The most common reasons for the failure of RC restorations were secondary caries, restoration fracture, and tooth fracture. For AM, the most common reasons for failure were secondary caries and tooth fracture. Conclusions: The quality of the evidence was low. The scarcity of studies comparing RC and AM in complex restorations has resulted in insufficient evidence to substantiate superior performance by either material.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.035 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".