A systematic review on the implication of Candida in peri-implantitis
Bibliographic record
Abstract
BACKGROUND: Candida is a heterogeneous fungal genus. Subgingival sulcus is a refuge for Candida, which has already been related to the pathogenic inflammation of periodontitis. This work aims to review the presence of Candida in the sulcular fluid surrounding dental implants and discuss its potential role in peri-implantitis. RESULTS: A bibliographical research was performed in PubMed, Scopus and Web of Science databases, with the keywords candida, peri-implantitis, periimplantitis, "dental implant" and implant. Newcastle-Ottawa Scale was used to assess the methodological quality of the included studies. At the end, nine observational studies were included, which analysed 400 dental implants with PI and 337 without peri-implantitis. Presence of Candida was assessed by traditional microbiological culture in blood agar or/and CHROMagar, though identification was also detected by quantitative real-time PCR, random amplified polymorphic DNA or ATB ID 32C. Dentate individuals and implants with peri-implantitis (range, 3-76.7%) had a bigger presence of Candida. C. albicans was the most isolated species, followed by Candida parapsilosis, Candida tropicalis, and Candida dubliniensis. CONCLUSION: Candida is part of the microbiological profile of the peri-implant sulcular fluid. More studies are needed to compare the link between Candida and other microorganisms and to discover the true role of these fungi in peri-implantitis.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.012 | 0.014 |
| 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) | 0.005 | 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".