Influence of maxillary antrolith on the clinical outcome of implants placed simultaneously with osteotome sinus floor elevation: A retrospective radiographic study
Bibliographic record
Abstract
BACKGROUND: Large antroliths and those located adjacent to the sinus floor can affect clinical interventions and increase the difficulty of implant placement performed simultaneously with osteotome sinus floor elevation surgery. PURPOSE: This retrospective study investigated the clinical outcomes of implants placed simultaneously with osteotome sinus floor elevation subjacent to maxillary antroliths. MATERIAL AND METHODS: Twenty implants inserted subjacent to or intruding into the antrolith after sinus floor elevation were evaluated in 18 patients. Cone-beam computed tomography (CBCT) was used to measure antrolith size and membrane thickness at sites of osteotome sinus floor elevation. Periapical radiographs were used to assess the height of grafted bone. Generalized estimating equation (GEE) analysis was performed to correlate the occurrence of antroliths with patient background characteristics and dental outcomes, based on a sample population of 239, among whom 33 presented antroliths. RESULTS: The 20 implants remained clinically stable over a mean follow-up period of 42.4 months. The mean thickness of the sinus membrane at osteotome sites was 5.4 ± 3.3 mm. None of the cases presented sinus membrane perforation or sinus symptoms following osteotome intervention. The mean gain in the height of grafted sinus bone was 4.0 ± 1.4 mm at the last follow-up. The occurrence of antroliths was higher among females and the elderly (>49 years old). The multivariable GEE analysis showed that the adjusted odds ratio for the occurrence of antroliths with root canal fillings was significantly lower than those without root canal fillings (odds ratio = 0.33; 95% confidence interval = 0.11-0.96). CONCLUSION: Our findings indicate that osteotome sinus floor elevation is a surgical procedure with a risk <17%. Thorough planning based on CBCT and careful management during surgery can eliminate the negative effects of antroliths on implant performance.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".