Onlays/partial crowns versus full crowns in restoring posterior teeth: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Tooth-colored onlays and partial crowns for posterior teeth have been used increasingly in clinics. However, whether onlays/partial crowns could perform as well as full crowns in the posterior region was still not evaluated thoroughly. Methods A literature search was conducted without language restrictions in Pubmed, Embase, Cochrane Central Register of Controlled Trial and Web of science until September 2021. RCTs, prospective and retrospective observational studies with a mean follow-up of 1 year were selected. Cochrane Collaboration’s tool was adopted for quality assessment of the RCT. The quality of observational studies was evaluated following Newcastle-Ottawa scale. The random-effects and fixed-effects model were employed for meta-analysis. Results Four thousand two hundred fifty-seven articles were initially searched. Finally, one RCT was identified for quality assessment and five observational studies for qualitative synthesis and meta-analysis. The RCT was of unclear risk of bias while five observational studies were evaluated as low risk. The meta-analysis indicated no statistically significant difference in the survival between onlays/partial crowns and full crowns after 1 year (OR = 0.55, 95% CI: 0.02-18.08; I2 = 57.0%; P = 0.127) and 3 years (OR = 0.65, 95% CI: 0.20-2.17; I2 = 0.0%; P = 0.747). For the success, onlays/partial crowns performed as well as crowns (OR = 0.58, 95% CI: 0.20-1.72; I2 = 0.0%; P = 0.881) at 3 years. No significant difference of crown fracture existed between the two methods (RD = 0.00, 95% CI: − 0.03-0.03; I2 = 0.0%; P = 0.972). Conclusions Tooth-colored onlays/partial crowns performed as excellently as full crowns in posterior region in a short-term period. The conclusions should be further consolidated by RCTs with long-term follow-up.
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.039 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".