The relationship between matrix metalloproteinases-8 and peri-implantitis: A systematic review and meta-analysis
Bibliographic record
Abstract
Peri-implantitis diagnosis typically involves evaluating inflammation, pocket depth, bleeding, and bone loss around dental implants. Although these methods are reliable and convenient, they mainly determine the history of the disease instead of the current activity or disease susceptibility. This meta-analysis evaluates whether the matrix metalloproteinase (MMP)-8 level in the peri-implant crevicular fluids (PICF) can be associated with peri-implantitis. The research was conducted in February 2022, where three electronic databases were searched and complemented with a manual search. The search criteria included original cross-sectional and longitudinal studies that compared MMP-8 biomarkers in crevicular fluids around healthy implants with unhealthy implants (peri-implantitis). To assess the risk of bias, the Newcastle-Ottawa Quality Scale was used. The data was analyzed using the RevMan program, and the standardized mean difference (SMD) with a 95% confidence interval was applied to evaluate the MMP-8 levels, with a significance level of p less than 0.05. Out of 1978 studies, six were eligible. This meta-analysis included 276 patients divided into two groups; 121 patients (124 implants) in the peri-implantitis group and 155 patients (156 implants) in the health implants group. The quality of the included studies was evaluated as high to moderate. The meta-analysis showed a significant increase in MMP-8 levels in individuals with peri-implantitis compared to those with healthy implants (SMD = 1.43, 95% CI [0.19, 2.68], p = 0.02). The current meta-analysis found that the levels of MMP-8 in PICF were significantly elevated in peri-implantitis cases compared to healthy controls, indicating a potential link between MMP-8 and peri-implantitis. However, the meta-analysis does not provide evidence for MMP-8 as a diagnostic test for peri-implantitis. Further research, specifically diagnostic accuracy studies, is needed to establish the value of MMP-8 as a diagnostic tool for peri-implantitis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".