Longevity of Amalgam Versus Composite Resin Restorations in Permanent Posterior Teeth: A Systematic Review
Bibliographic record
Abstract
The present systematic review aims to compare the longevity of amalgam and composite resin restorations in adult human posterior permanent teeth, evaluating clinical performance, survival rates, failure causes, and influencing factors. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a comprehensive search was conducted in PubMed, Scopus, Web of Science, and other databases. Studies were included if they assessed the longevity of amalgam and composite resin restorations in adult posterior teeth with at least one year of follow-up. The Newcastle-Ottawa Scale (NOS) and Cochrane Risk of Bias (ROB) tool were used for the assessment of risk of bias. Eight studies (2003-2023) met the inclusion criteria, comprising randomized clinical trials, prospective, retrospective, and cross-sectional studies. Amalgam restorations exhibited superior longevity, with median survival times exceeding 16 years, compared to 11 years for composite restorations. Secondary caries was the most common cause of composite failure, whereas fracture was the primary reason for amalgam replacement. Patient factors, including oral hygiene and bruxism, significantly influenced restoration longevity. Amalgam restorations demonstrate greater durability than composite resins in posterior teeth. However, aesthetic preferences and advancements in composite materials continue to drive their usage. Future research should focus on improving composite longevity to provide viable alternatives to amalgam.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".