Peri-implant diseases and metabolic syndrome components: a systematic review.
Bibliographic record
Abstract
OBJECTIVE: Metabolic syndrome (MetS) is defined as a spectrum of conditions associated with an increased risk of developing CVD and type 2 diabetes. MetS include: hyperglycemia, hypertension, visceral obesity, dyslipidemia with elevated values of triglycerides (TG) and low levels of HDL. The aim of this review is to provide current knowledge of the relationship between MetS, its components and peri-implant diseases. MATERIALS AND METHODS: An electronic literature search was conducted in the English language in several databases. The Newcastle-Ottawa Scale was used for quality assessment of cohort and cross-sectional studies; while systematic reviews were evaluated through AMSTAR; results were reported according to the PRISMA Statement. RESULTS: A total of 272 records were identified through database searching, six studies were included for qualitative analysis. No study directly related to MetS was found, there was inconsistent and controversial evidence regarding association with cardiovascular disease. A higher risk of peri-implantitis was detected in people with hyperglycemia. CONCLUSIONS: Future research should be orientated in assessing the risk of peri-implant diseases, evaluating patient's therapeutic response, analyzing directionality of the relationship between MetS, its components and biologic implant 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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| 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 | 0.000 |
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".