Longevity of Crown Margin Repairs Using Glass Ionomer Cement: A Retrospective Study
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to determine the survival time of crown margin repairs (CMRs) with glass ionomer and resin-modified glass ionomer cements on permanent teeth using electronic dental record (EDR) data. METHODS: We queried a database of EDR (axiUm; Exan Group, Coquitlam, BC, Canada) in the Indiana University School of Dentistry (IUSD), Indianapolis, IN, USA, for records of patients who underwent CMRs of permanent teeth at the Graduate Operative Dentistry Clinic. Two examiners developed guidelines for reviewing the records and manually reviewed the clinical notes of patient records to confirm for CMRs. Only records that were confirmed with the presence of CMRs were retained in the final dataset for survival analysis. Survival time was calculated by Kaplan-Meier statistics, and a Cox proportional hazards model was performed to assess the influence of age, gender, and tooth type on survival time (a<0.05). RESULTS: A total of 214 teeth (115 patients) with CMR were evaluated. Patient average age was 69.4 ± 11.7 years old. Posterior teeth accounted for 78.5% (n=168) of teeth treated. CMRs using glass ionomer cements had a 5-year survival rate of 62.9% and an annual failure rate (AFR) of 8.9%. Cox proportional-hazards model revealed that none of the factors examined (age, gender, tooth type) affected time to failure. CONCLUSION: The results indicate the potential of CMRs for extending the functional life of crowns with defective margins, thus reducing provider and patient burden of replacing an indirect restoration. We recommend future studies with a larger population who received CMR to extend the generalizability of our findings and to determine the influence of factors such as caries risk and severity of defects on survival time.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".