A 30-year retrospective study of single-unit and splinted implant supported crowns and their effects upon adjacent tissues and teeth in a Canadian Dental School Environment
Bibliographic record
Abstract
Objective: A retrospective study at a Canadian dental school evaluated the survivability of single-unit and splinted implant supported crowns and their effects on adjacent tissues. Methods: Data from patients of all ages was collected from the institution’s computer patient management software (AxiUm) and physical charts. Results: A total of 678 implant supported crowns (586 single-unit and 92 splinted) were placed at the University of Manitoba Dr. Gerald Niznick College of Dentistry between September 10, 1989 to January 1, 2020. Of the implant cases, 249 (36.7%) of them were smokers, 64 (9.44%) were diabetic and 96 (14.2%) were reported to experience bruxism. Within the duration of the study, 17 (2.90%) single-unit crowns and 5 (5.43%) splinted crowns failed and warranted a replacement. Furthermore, 371 single-unit (63.3%) and 46 splinted (50.0%) implant crowns were a complete success as they had no complications with the crown itself or adjacent tissues. Therefore, 215 single-unit (36.7%) and 46 splinted (50.0%) crowns endured some type of complication with the crown or adjacent tissues which may have led to its failure. Overall, 96.8% of cases experienced no failure as of the study end date and a log rank test was performed to determine if there were differences in the survival distribution for the single-unit and splinted implant supported crowns (χ2(2) = 1.285, p = 0.257). Conclusion: The survival distribution of single-unit and splinted implant supported crowns was not statistically significant as they both presented with high success rates and minimal complications. Although some limitations and challenges were present, this study highlights the longevity and complications of implant supported crowns in order to improve their functionality and lifespan as well as to maintain the health of adjacent teeth.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".