Long‐term effects of sinus membrane perforation on dental implants placed with transcrestal sinus floor elevation: A case–control study
Bibliographic record
Abstract
BACKGROUND: There is a little comparative data on implants placed transcrestally with/without sinus membrane (SM) perforation. PURPOSE: To compare the clinical and radiological outcomes of implants with maxillary sinus perforation and those without SM perforation. MATERIALS AND METHODS: Among 560 transcrestally placed implants in 324 patients, the patients who underwent cone-beam computed tomographic radiography (CBCT) were included. The following groups were established: implants with SM perforation (group P) and implants without SM perforation based on postoperative panoramic radiographs and patient records (group NP). Group NP was further divided into subgroups based on CBCT taken at the last patient visit: group NP1 consisting of implants with no protrusion or <1 mm of protrusion and group NP2 consisting of implants with ≥1 mm of protrusion. Mixed linear regression was performed for the factors affecting SM thickening and marginal bone loss. Mixed survival analysis was also performed. RESULTS: A total of 379 implants in 221 patients were eligible. The mean follow-up period was 112.03 ± 54.2 months. Twenty-six implants failed (2 and 24 implants in groups P and NP, respectively), mainly due to peri-implant bone loss. No statistically significant difference was noted between the groups in SM thickness (2.4 ± 2.8 mm, 2.1 ± 3.4 mm, and 2.5 ± 3.5 mm in groups P, NP1, and NP2, respectively, p > 0.05). Marginal bone loss in group NP1 was significantly greater than that in the other groups. In the mixed model, SM perforation was not a determinant of sinus membrane thickening and implant survival in the mixed models and the survival analysis, respectively. CONCLUSIONS: SM perforation in transcrestal sinus augmentation did not affect implant survival and SM thickening.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".