Tooth‐to‐Implant Connection: A Systematic Review of the Literature and a Case Report Utilizing a New Connection Design
Bibliographic record
Abstract
BACKGROUND: In the treatment of partially edentulous patients, implants have often been connected to natural teeth. Numerous studies have reported significant complications and problems, while others have demonstrated favorable outcomes. PURPOSE: The purpose of this article was to systematically review the literature regarding the splinting of implants and teeth. The difference in the biomechanical behavior between osseointegrated implants and teeth and the efficacy of the different modes of connection that have been employed are explored. MATERIALS AND METHODS: A MEDLINE search between 1966 and October 2006 was performed to retrieve relevant articles. A further manual search from the bibliographies of the former articles was performed to include as many references as possible. Prospective and retrospective clinical studies, as well as laboratory and computer-generated research, were included. RESULTS: A pronounced difference in the biomechanics of teeth and implants has been revealed in theoretical models. This disparity has also been supported by the majority of the experimental work published. As a result, principal complications, such as intrusion of teeth and higher risk of overload and greater marginal bone loss around the implants have been reported. Among the several types of connections utilized, the rigid connection showed fewer complications but unfortunately did not eliminate them. CONCLUSION: Totally implant-supported prostheses should be the treatment of choice. However, there are cases where combining teeth and implants is inevitable. The authors propose a rationale design of connecting implants and teeth. This design minimizes the biologic and technical complications.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.019 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".