Platform switch hybrid zygoma implants improve prosthetics and marginal bone protection after extra‐sinus placement
Bibliographic record
Abstract
PURPOSE: The aim of our studdy is clinical evaluation of Platform switch hybrid zygoma implants. MATERIALS AND METHODS: 117 zygomatic implants were followed up during this time. They included 55 Brånemark System zygoma implants, 38 Noris implants, and 24 novel iRES hybrid implants with platform switch. RESULTS: Bone quality and quantity are the prerequisite for successful implant treatment. Zygomatic implants are intended for patients with severely resorbed maxilla that cannot accommodate conventional implants without prior extensive bone grafting. Such regenerative procedures, like sinus lifts, prolong implant rehabilitation to several months (12-18). Furthermore, extensive grafts are less predictable showing varying degrees of graft resorption. Zygoma implants enable full, often immediate, reconstruction of the upper dental arch without the need for sinus lift treatment. The original zygoma protocol runs the implants through the sinus, requires general anesthesia, and positions the prosthetic platform of the implants on the palate, which makes prosthesis cumbersome. It also induces risk for post-op sinusitis. Extra-sinus approach with novel zygoma hybrid implants bypasses sinuses and positions the implant prosthetic platform on the crest allowing for same good prosthetics as on conventional dental implants. Furthermore, crestal threads and a platform-switch, of the novel zygoma design, increase implant anchorage and minimize marginal bone loss. The study presents evolution of zygoma implant rehabilitation protocol and zygoma implant design in our clinical practice over 15 years (2004-2019). CONCLUSION: Extra-sinus zygomatic implant placement lowers the risk of post-op sinusitis and makes procedure possible to be done in local anesthesia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.003 | 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".