Peri-Implantitis: A Review of the Disease and Report of a Case Treated with Allograft to Achieve Bone Regeneration
Bibliographic record
Abstract
Dental implants offer excellent tooth replacement options however; peri-implantitis can limit their clinical success by causing failure.Peri-implantitis is an inflammatory process around dental implants resulting in bone loss in association with bleeding and suppuration.Dental plaque is at the center of its etiology, and in addition, systemic diseases, smoking, and parafunctional habits are also implicated.The pathogenic species associated with peri-implantitis include, Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, and Tannerella forsythia.The goal in the management of peri-implantitis is the complete resolution of peri-implant infection with function.Therapies using various biomaterials to deliver antibiotics have been used in the treatment of peri-implantitis e.g.fibers, gels, and beads.The use of guided tissue regeneration barrier membranes loaded with antimicrobials has shown success in re-osseointegrating the infected implants in animal models.Several uncertainties still remain regarding the management of peri-implantitis.The purpose of this article is to present a background of peri-implantitis along with a case of peri-implantitis successfully treated for bone regeneration.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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".