Three‐year clinical prospective follow‐up of extrasinus zygomatic implants for the rehabilitation of the atrophic maxilla
Bibliographic record
Abstract
BACKGROUND: Placement of extrasinus zygomatic implants to support implant-supported rehabilitation is still controversial due to the scarcity of data. PURPOSE: To evaluate the clinical outcomes of 94 extrasinus zygomatic implants, installed laterally to the maxillary sinus, for rehabilitation of the edentulous atrophic maxillae. MATERIALS AND METHODS: A total of 42 patients (mean age 58 years) with severely atrophic maxillae were treated between November 2010 and July 2011, and followed up until July 2014. A total of 273 implants (94 zygomatic implants and 179 conventional implants) were used. The patients were followed in a standardized clinical and radiographic method. RESULTS: During the 3-year study period, 1 zygomatic implant and 4 conventional implants failed, resulting in a survival rate of 98.9% and 97.7% respectively. All restorations with titanium-welded bars were installed either 3 days after surgery (immediate loading) or 6 months after surgery (delayed loading), and were successful until the last follow-up appointment, except for minor technical problems. No patient presented any type of sinus adverse event. No other significant occurrences were reported. CONCLUSION: This 3-year clinical follow-up study indicates that extrasinus zygomatic implants represent predictable treatment option atrophic maxillae. Further longitudinal prospective clinical studies are necessary to confirm these results.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".