Implant‐Supported Immediately Loaded Fixed Full‐Arch Dentures: Evaluation of Implant Survival Rates in a Case Cohort of up to 7 Years
Bibliographic record
Abstract
BACKGROUND: The treatment of severely atrophied and edentulous jaws by means of fixed implant supported solutions is a challenging procedure. PURPOSE: The immediate loading of four to six axial and tilted implants offers the possibility to overcome elaborate hard tissue augmentation procedures but lacks implant and patient related data on implant survival rates. MATERIALS AND METHODS: This retrospective 7-years clinical trial investigated the implant survival rates of 2,081 implants (380 patients, 482 jaws) using an immediate loading protocol with either 4, 5, or 6 implants per restoration. Survival rates were calculated concerning implantation related factors (jaws/number of supporting implants/angulations/diameters/lengths) and patient related factors (medical status/smoking). RESULTS: Overall survival of 2,081 implants was 97.0% on implant level. Survival rates of implantation related factors did not yield significant differences. Significant differences were yield between healthy patients and patients with osteoporosis (p = .002) and the medical status group "other" (p = .032), respectively. Smokers yielded a significantly higher survival than nonsmokers (p = .002). CONCLUSIONS: It is assumed that four implants per jaw serve as a sufficient implant number for full arch restorations in both, the mandible and the maxilla. Osteoporosis under the medication with bisphosphonates seems to be a risk factor for implant survival. The authors suggest that the effect of smoking on ISRs remains controversial within this treatment concept.
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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 | 0.000 |
| 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".