Recent Trends in Sinus Lift Surgery and Their Clinical Implications
Bibliographic record
Abstract
BACKGROUND: Sinus lift procedures are used to allow residual bone to accommodate functional implants in atrophic posterior maxilla. Numerous anatomical and surgical advancements in sinus lift surgery are still inspiring clinicians. PURPOSE: The purpose of this study was to describe the recent trends in sinus lift surgery focusing on implant survival, bone grafting, anatomical and surgical considerations, and their clinical implications on the practice of implant dentistry in atrophic posterior maxilla. MATERIALS AND METHODS: We performed an extensive search in MEDLINE, Embase, Scopus, Web of Science, Trip, Cochrane Oral Health Group's Trials Register, Cochrane Central Register of Controlled Trials, and ProQuest Dissertations & Theses. Articles were critically reviewed to determine the level of evidence as per the Canadian Task Force on Preventive Health Care. RESULTS: Comprehensive assessment of sinus septa, sinus pathology, and bone quality and quantity using three-dimensional cone beam computed tomography radiographs is important before placing implants in posterior maxilla. With a residual bone height of less than 5 mm, the survival rate of implant decreases substantially. Lateral window approach can increase the vertical bone height to greater than 9 mm, while osteotome approach can increase this height from 3 to 9 mm. The perforation of Schneiderian membrane doubles the risk for the incidence of sinusitis or infection. The use of piezoelectric surgery allows adequate sinus lift while protecting soft tissues and minimizing patient discomfort. CONCLUSIONS: Although both osteotome and lateral window procedures can help clinicians in overcoming the challenges of placing implants in atrophic posterior maxilla, pre-implant residual bone height is crucial in determining the survival of these implants. Future research directions should consider study designs grounded on longitudinal randomized controlled trials of large sample size.
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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 | 0.010 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".