Evaluation of Zirconia‐Based All‐Ceramic Single Crowns and Fixed Dental Prosthesis on Zirconia Implants: 5‐Year Results of a Prospective Cohort Study
Bibliographic record
Abstract
OBJECTIVE: The objective of this 5-year cohort investigation was to determine the survival and success rate of all-ceramic reconstructions on zirconia oral implants. MATERIAL AND METHODS: Ninety-three patients received 122 one-piece zirconia implants. One hundred seventeen implants were restored with 63 single crowns (SCs) and 27 three-unit bridges (fixed dental prostheses, FDPs) fabricated using zirconia frameworks (Procera(®) Zirconia, Nobel Biocare(®), Göteborg, Sweden) hand-layered with a silicate ceramic (NobelRondo(™) Zirconia, Nobel Biocare(®)). With any occurrence of chipping regarded as an event, Kaplan-Meier success curves were plotted. Covariates (gender, location, manufacturing date) were estimated by the use of log-rank tests. RESULTS: Eighty-nine patients received prosthetic reconstructions. Sixty-three of them were seen at the 5-year follow-up, with a mean observation time of 58.2 months (47 patients with SCs, 16 patients with FDPs). Reasons for the decreasing number of patients at the follow-up sessions included dropouts due to implant loss (n = 21), moving (n = 3), missed appointments (n = 1), and severe illness (n = 1). Over half of the SCs (57.2%) and 38% of the FDPs were successful after an observation time of 5 years (overall success rate of 51.7%). The performed log-rank tests revealed no statistically significant differences for the success curves regarding the above-mentioned covariates. Among the 63 restorations that completed the study, 11 of 47 SCs and one of 16 FDPs had to be replaced due to the severity of the observed chipping. This results in survival rates of 76.6% for the SCs and 93.8% for the FDPs. No framework fractures or decementations were observed in any group. CONCLUSION: Hand-layering of zirconia-based SCs and FDPs with NobelRondo(™) Zirconia restoring one-piece zirconia implants did not show acceptable survival and success rates. Meanwhile, the material has been recalled from the market. It is advised that new materials should undergo adequate preclinical evaluation before coming to the market.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".