Clinical outcomes of dental implants placed in the augmented maxillary sinus: A 5-year retrospective study
Bibliographic record
Abstract
ABSTRACT Background: Factors influencing the success of an implant placed in augmented maxillary sinus need to be recognized. The aim of this study was to investigate the effect of various oral health conditions and treatment plan details on the clinical and radiographical outcomes of implants placed in the augmented sinus. Materials and Methods: In this clinical retrospective study, 39 participants (81 implants) that received dental implants after sinus lifting between January 2005 and July 2016 were evaluated. All the participants were examined by an operator clinically and radiographically in a blinded manner. A checklist including oral health and host condition, implant and prosthesis characteristics, and surgical approach variables was completed for each participant. The effect of these variables on probing depth (PD), marginal bone loss, bone formation in sinus, and patient satisfaction was analyzed using analysis of covariance models. P <0.05 was considered statistically significant. Results: Survival rates after surgery and restoration placement were 93% and 100%, respectively. PD was found to be significantly higher in restorations with infragingival finish lines over 1.5 mm and in implants with score “2” for gingival index. Moreover, more bone formation was observed in implants with score “0” compared with score “2” for gingival index. In addition, the participants with plaque score “0” reported significantly more satisfaction than the participants with score “2” for plaque index. Conclusion: Inflamed gingiva was associated with more PD and less peri-implant bone formation in maxillary sinus. In addition, more patient satisfaction was reported by participants that had better plaque control.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".