Implant connection and abutment selection as a predisposing and/or precipitating factor for peri‐implant diseases: A review
Bibliographic record
Abstract
Peri-implant mucosal integration is becoming a critical aspect for long term implant health and can be triggered the selection of implant components. The aim of this review is therefore to investigate the evidence concerning implant connection and abutment characteristics (abutment materials, design, handling) as predisposing or precipitating factor for peri-implant mucositis and peri-implantitis. Although the evidence that these features can directly predispose/precipitate peri-implant diseases is limited, there are -few- studies showing a potential role of the implant connection, trans-mucosal configuration, and handling in the development of early bone loss and/or peri-implantitis. With bone level implants, conical internal connections (with inherent platform switching) might be preferred over internal flat-flat and external connections to decrease the risk of early bone loss and potentially the risk of peri-implant disease. Moreover, there is a trend suggesting moving the prosthetic interface coronally (to the juxta-mucosal level) as soon as possible to reduce the number of disconnections and to limit the risk of cements remnants. This can be achieved by choosing a tissue-level implant or to place a trans-mucosal abutment (one abutment-one time approach) to optimize the peri-implant soft tissue seal. In absence of evidence for the biocompatibility regarding several restorative materials, biocompatible materials such as titanium or zirconia should be preferred in the trans-mucosal portion. Finally, higher implants (≥2mm) with an emergence angle below 30° seem more favourable. It should however be noted that some of this information is solely based on indirect information (such as early bone loss) and more research is needed before making firm recommendations about abutment choice. [Correction added on 13 March 2023, after first online publication: 'longer implants (≥2mm)' was changed to 'higher implants (≥2mm)' in this version.].
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".