A Retrospective Clinical Study with Regard to Survival and Success Rates of Zirconia Implants up to and after 7 Years of Loading
Bibliographic record
Abstract
PURPOSE: The study aims to retrospectively investigate the clinical performance of first-generation zirconia implants with a sandblasted surface up to and after 7 years of loading. MATERIALS AND METHODS: Clinical records of patients treated with zirconia implants between 2004 and 2009 were screened. Consequently, adequate patients were invited to a clinical and radiographic investigation to classify each implant according to strict success criteria. RESULTS: Seventy-one patients receiving 161 implants were available for the evaluation. Overall, 36 implants (22.4%) were lost due to early (n = 14) and late failures (n = 4) or fractures (n = 18). All surviving 125 implants fulfilled the success criteria. None of the investigated implants had a history of peri-implant infections. Mean values with regard to gingival index, plaque index, modified sulcus bleeding index, and probing depth were 0.03, 0.23, 0.59, and 2.80 mm, respectively. The radiographically evaluated mean crestal bone loss was 0.97 ± 0.07 mm. Diameter-reduced implants (3.25 mm) showed lower survival (58.5%) compared with implants with a diameter of 4.0 mm (88.9%) and 5.0 mm (78.6%). The overall longitudinal survival rate was 77.3%. CONCLUSIONS: First-generation zirconia implants showed low overall survival and success rates. The evaluated clinical and radiographic parameters were consistent with healthy peri-implant tissues. Additionally, nonfractured failures were not associated with peri-implant infections.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".