Longevity of Crown Margin Repairs Using Glass Ionomer: A Retrospective Study
Why this work is in the frame
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Bibliographic record
Abstract
Objectives: Repair of crown margins may extend the functional life of existing crowns. However, the longevity of such treatment is unknown. This study determined the survival time of crown margin repairs (CMR) with glass-ionomer (GI) and resin-modified glass-ionomer cements. Methods: We queried axiUm (Exan Group, Coquitlam, BC, Canada) database for permanent teeth that underwent CMR in the Graduate Operative Dentistry Clinic, Indiana University School of Dentistry (IUSD), Indianapolis, Ind., USA, from January 1, 2006 through January 1, 2018. Since there is no CDT code for the CMR procedure, CDT codes for resin-composite and GI restorations (D23XX) were queried; these patients also had treatment notes that indicated CMR. The final data set included patient ID, birth date, gender, dates of treatments, CDT codes, tooth type, tooth surface and existing findings. Two examiners developed guidelines for record review and manually reviewed the clinical notes of patient records to confirm CMR. Only records that were confirmed with the presence of CMR 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 selected variables (p < 0.05). Results: 214 teeth (115 patients) with CMR were evaluated. Patient average age was 69.4 11.7 years old. Posterior teeth accounted for 78.5 percent (n = 168) of teeth treated. CMRs using GI had a projected 5-year survival rate of 62.9 percent (K-M Analysis) and an 8.9 percent annual failure rate. Cox Proportional Hazards Regression analysis revealed that none of the factors examined (age, gender, tooth type) affected time to failure. Conclusion: CMRs may extend the longevity of crowns with defective margins. Larger EHR studies or case control studies are needed to investigate other variables, such as the caries risk status or the severity of defects that may affect the survival rate of CMRs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it