Displacement of Dental Implants Into the Maxillary Sinus: A Retrospective Study of Twenty‐One Patients
Bibliographic record
Abstract
BACKGROUND: One possible complication of implant surgery in the posterior maxilla is the displacement of implants into the maxillary sinus. PURPOSE: To report on clinical and radiological findings and on biological, surgical, and biomechanical considerations in cases of implant displacement. MATERIALS AND METHODS: This is a retrospective study of 21 patients referred to the Department of Head and Neck Surgery, Second University of Naples, due to implants displaced into the maxillary sinus. Patient, implant, and treatment data were collected, and 1-year follow-up was made. RESULTS: A total of 24 displaced implants were diagnosed and surgically removed through an antrostomy in the lateral sinus wall. Implant displacement occurred after functional loading in only one case; in the remaining cases, displacement occurred either perioperatively or postoperatively prior to loading. Besides the displacement, eight patients suffered from maxillary sinusitis, treated with a Caldwell-Luc operation. Healing was uneventful for all patients, and no sinusitis relapse or late postoperative complication was present at 1-year follow-up. CONCLUSIONS: It is reasonable to affirm that the major cause of displacement of implants is related, most of the time, to incorrect treatment planning and/or a poorly performed surgical procedure. When implant displacement occurs, the displaced foreign body has to be removed in order to avoid sinus pathology.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".