Salivary matrix metalloproteinases in periodontitis and cardiovascular disease: a systematic review
Bibliographic record
Abstract
This systematic review aimed to synthesize findings from existing studies to explore the role of matrix metalloproteinases (MMPs), particularly MMP-9 and MMP-8, in the pathophysiology of cardiovascular disease (CVD) and periodontitis. A comprehensive literature search was conducted across multiple electronic databases, including Medline, Scopus, Embase, Epistemonikos, and grey literature sources. Cross-sectional, cohort, and case-control studies that evaluated salivary MMP levels in patients with periodontitis and CVD were included. The Newcastle-Ottawa Scale was used to assess the quality and risk of bias of the included studies. Confounding factors were evaluated using a causal diagram and a confounder matrix. Eight studies with a total of 2,636 participants were included in the review. Elevated levels of salivary MMP-9 and MMP-8 were consistently observed in patients with both periodontitis and CVD, compared to healthy controls or patients with periodontitis alone. The imbalance between MMPs and their inhibitors, such as TIMP-1, was also evident in these patients, indicating dysregulated extracellular matrix remodeling. Salivary MMP levels were correlated with other inflammatory markers, including myeloperoxidase (MPO) and interleukin-1 beta (IL-1β), further supporting the interconnected nature of oral and systemic inflammation. This review highlights the potential of salivary MMPs, particularly MMP-9 and MMP-8, as biomarkers for the early diagnosis, risk stratification, and monitoring of the interrelated conditions of periodontitis and cardiovascular disease. Further, longitudinal studies are warranted to elucidate the causal relationships between these biomarkers and disease progression.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.010 | 0.010 |
| 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) | 0.004 | 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".