Association between diabetes mellitus/hyperglycaemia and peri‐implant diseases: Systematic review and meta‐analysis
Bibliographic record
Abstract
AIM: This systematic review investigates whether hyperglycaemia/diabetes mellitus is associated with peri-implant diseases (peri-implant mucositis and peri-implantitis). MATERIALS AND METHODS: Electronic and manual literature searching was conducted. An a priori case definition for peri-implantitis was used as an inclusion criterion to minimize risk of bias. The Newcastle-Ottawa Scale was used for quality assessment; random effect models were applied; and results were reported according to the PRISMA Statement. RESULTS: Twelve studies were eligible for qualitative and seven of them for quantitative analyses. Meta-analyses detected the risk of peri-implantitis was about 50% higher in diabetes than in non-diabetes (RR = 1.46; 95% CI: 1.21-1.77 and OR = 1.89; 95% CI: 1.31-2.46; z = 5.98; p < .001). Importantly, among non-smokers, those with hyperglycaemia had 3.39-fold higher risk for peri-implantitis compared with normoglycaemia (95% CI: 1.06-10.81). Conversely, the association between diabetes and peri-implant mucositis was not statistically significant (RR = 0.92; 95% CI: 0.72-1.16 and OR = 1.06; 95% CI: 0.84-1.27; z = 1.06, p = .29). CONCLUSIONS: Within its limits that demand great caution when interpreting its findings, this systematic review suggests that diabetes mellitus/hyperglycaemia is associated with greater risk of peri-implantitis, independently of smoking, but not with peri-implant mucositis.
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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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.022 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".