Retrospective analysis of dental implant fracture following loading: A retrospective clinical study
Bibliographic record
Abstract
STATEMENT OF PROBLEM: Fracture of an osseointegrated implant (FOI) is a rare complication that occurs primarily after loading and may lead to other complications including failure or fracture of the implant-supported prosthesis. Risk factors for FOI are not well understood. PURPOSE: The purpose of this retrospective clinical study was to determine the frequency of occurrence of FOI among participants treated with dental implants in an academic setting and to identify and analyze the possible risk indicators and contributing factors. MATERIAL AND METHODS: A retrospective analysis was performed using dental records of participants who received dental implant treatment at the Faculty of Dentistry, University of Toronto, from January 1979 until January 2020, and experienced post-loading FOI. A systematic search of the dental records was conducted, and clinical situations with FOI were identified. Data related to patient factors, implant factors, and prosthesis factors were collected from the identified clinical situations with FOI. The data were analyzed to determine the incidence of FOI. A descriptive analysis was used to identify the possible risk indicators for FOI. RESULTS: A total of 7712 implants had been placed at the Faculty of Dentistry, University of Toronto, from January 1979 until January 2020. During the 41-year period, a total of 27 fractured implants were identified. The incidence of FOI following loading was 0.35%. Overall, the mean ±standard deviation time between loading and occurrence of implant fracture was 10.6 ±7 years. Implant fractures occurred in 23 different study participants; 16 men, and 7 women, with a mean ±standard deviation age of 65.4 ±8.0 years at the time of FOI. Factors associated with implant fracture include narrow-diameter implants (≤3.75 mm), implants placed in posterior mandible (molar or premolar regions), presence of a long cantilever, and unfavorable implant design (such as the Tri-Channel design). Among the 27 fractured implants, 19 were removed, 6 were buried, and 2 were adjusted or smoothed and restored with a new prosthesis. CONCLUSIONS: The incidence rate of FOI was very low, but might have been increased by an increased presence of predisposing risk factors.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".