Mucosal cyst aspiration in conjunction with maxillary sinus elevation: A clinical cohort study
Bibliographic record
Abstract
INTRODUCTION: Patients with mucosal cysts in the maxillary sinus require special consideration in patients who require implant therapy for the restoration when undergoing implant therapy for the restoration of the posterior maxillary dentition. Treatment strategies for these clinical situations remain controversial in the literature. Thus, this study seeks to describe a safe and effective therapeutic strategy for sinus augmentation in patients with pre-existing maxillary antral cysts. METHODS: A total of 15 patients and 18 sinuses were consecutively enrolled in this cohort study and underwent maxillary antral cyst treatment by needle aspiration and simultaneous maxillary sinus augmentation (MSA). During surgical procedures, threeimplants (Zimmer Biomet, Indiana, USA) were positioned in 11 sinuses and two implants (Zimmer Biomet, Indiana, USA) were positioned in 5 sinuses. RESULTS: Overall implant success and survival rates were 100% and 97.8%, respectively at 1 year and 5-year follow-ups. Crestal bone resorption averaged 0.3 ± 0.2 mm 5-year post-loading, showing bone stability. Implant survival rate at 5-year follow-up expressed predictability of the technique comparable to historical data when MSA was performed alone. Crestal bone resorption averaged 0.3 ± 0.2 mm 5 years post-loading and shows bone stability utilizing mucosal cyst aspiration with concomitant MSA procedures. Quality of life evaluation at 1-week post-op showed similar results to published historical data. In 81% (13 sinuses), the CBCT examination at 5-year follow-up showed no cyst reformation, in 19% (3 sinuses) cyst reformation was visible, but smaller in size when compared to the pre-op CBCT evaluation, and all the patients were asymptomatic. CONCLUSIONS: Maxillary sinus mucosal cyst aspiration with concomitant MSA, may be a viable option to treat maxillary sinus cyst.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".