Longitudinal reactions of maxillary sinus in patients treated with multiple zygomatic implants: A modified radiographic evaluation with clinical follow‐up
Bibliographic record
Abstract
OBJECTIVES: To investigate the effects of zygomatic implant placement on the maxillary sinus using radiographic and clinical indicators. METHODS: Patients with an atrophic maxilla who underwent zygomatic implant placement were included. The thickness and morphology of the Schneiderian membrane (SM), infundibular obstruction, and posterior bone wall of the maxillary sinus were analyzed. The generalized estimating equation and chi-square tests were performed to compare the measurements. RESULTS: Fifty patients with 100 maxillary sinuses were included. In total, 148 zygomatic implants and 105 regular implants were placed in the maxilla. Overall, the mean pre- and postoperative SM thickness was 2.79 ± 3.26 mm and 3.97 ± 5.45 mm, respectively (p = 0.063). In sinuses with two zygomatic implants, the SM thickness increased significantly from 2.12 ± 2.14 mm preoperatively to 4.07 ± 6.14 mm postoperatively (p = 0.026). The number of sinuses with type IV morphology (fully radiopaque) increased from zero preoperatively to six (13%) postoperatively. Sinuses with a single zygomatic implant showed no difference in the pre- and postoperative SM thickness. Postoperatively, six sinuses had infundibulum obstructions. Postoperative osteitis of the bilateral sinuses was found in two patients. CONCLUSIONS: We have proposed a new imaging evaluation method and system for evaluating the maxillary sinus response. Preoperative infundibulum obstruction combined with mucosal thickening and double zygomatic implant placement are more likely to induce postoperative maxillary sinus mucositis and osteitis.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".