Variations in survival time for amalgam and resin composite restorations: a population based cohort analysis.
Bibliographic record
Abstract
OBJECTIVE: To estimate the association between the restorative material used and time to further treatment across population cohorts with universal coverage for dental treatment. BASIC RESEARCH DESIGN: Cohort study of variation in survival time for tooth restorations over time and by restoration material used based on an Accelerated Failure Time model. CLINICAL SETTING: Primary dental care clinics. PARTICIPANTS: Members of Canada's First Nations and Inuit population covered by the Non-Insured Health Benefits program of Health Canada for the period April 1, 1999 to March 31, 2012. INTERVENTION: Tooth restorations using resin composite or amalgam material. MAIN OUTCOME: Survival time of restoration to further treatment. RESULTS: Median survival time for resin composite was 51 days longer than amalgam, for restorations placed in 1999-2000. This difference was not statistically significant (p⟩0.05). Median survival times were lower for females, older subjects. Those visiting the dentist annually, and decreased monotonically over time from 11.2 and 11.3 years for resin composite and amalgam restorations respectively placed in 1999-2000 to 6.9 and 7.0 years for those placed in 2009-10. CONCLUSIONS: Resin composite restorations performed no better than amalgams over the study period, but cost considerably more. With the combination of the overall decrease in survival times for both resin composite and amalgam restorations and the increase in use of resin composite, the costs of serving Health Canada's Non-Insured Health Benefits population will rise considerably, even without any increase in the incidence of caries.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".