Prevalence of Maxillary Sinus Pathology in Patients Considered for Sinus Augmentation Procedures for Dental Implants
Bibliographic record
Abstract
PURPOSE: To determine the prevalence of maxillary sinus pathology in patients presenting for implant rehabilitation involving sinus augmentation procedures. MATERIALS AND METHODS: Three-dimensional images of 275 patients were evaluated. Age and gender were recorded to see if they had any relationship to the prevalence of pathology. Scans were classified into 1 of the 5 categories based on the type of sinus pathology detected: healthy, mucosal thickening > 5mm, polypoidal mucosal thickening, partial opacification and/or air fluid level, and complete opacification. RESULTS: Overall, 54.9% scans were classified as healthy, and 45.1% scans were classified as exhibiting sinus pathology. Men were more likely to exhibit pathology compared with females (P < 0.01). However, age did not seem to have any relation on the prevalence of sinus pathology. Of the patients who presented with evidence of sinus pathology, 56.5% had mucosal thickening (≥ 5 mm), 28.2% with polypoidal thickening, 8.9% partial opacification and/or air/fluid level, and 6.5% complete opacification. CONCLUSIONS: It is proposed that, based on the findings of this study, 45.1% patients would require further consultation before proceeding with maxillary sinus augmentation surgery.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".