Is polymorphism inmetalloproteinases arisk factor for implantosseointegration failure?
Bibliographic record
Abstract
Aim: This study aimed to analyze if polymorphisms of metalloproteinases can influence endosseous implants’ osseointegration failure. Methods: This meta-analysis was registered in PROSPERO (CRD42020172108). The literature search was performed on Pubmed/MEDLINE, EMBASE, Scielo, BVS (LILACS and BVS Odontology), and Cochrane Controlled Trials databases. The gray literature and a manual search in periodicals of specific relevance to dentistry and the orthopedics field were also performed. Two calibrated reviewers read all titles and abstracts of the articles and selected those related to the theme. Then, the authors reviewed the full selected articles, fulfilling the inclusion and exclusion criteria. The inclusion and exclusion criteria were related to the type of study design, article language, and population characteristics. The quality of individual studies was evaluated using the Newcastle-Ottawa scale. A meta-analysis was performed using the MetaGenyo software to analyze the association between MMP SNPs and the risk of implant osseointegration failure. The Fixed Effects Model (FEM) and Random Effects Model (REM) were used depending on the amount of heterogeneity in the data. Results: Three hundred ninety-seven articles were screened, and nine studies were selected for the meta-analysis. The MMP-1 g.-1607 G>GG (rs1799750) is statistically associated with osseointegration failure as a protective factor (OR=0.15, 95% CI=0.05-0.45). The MMP-8 g.- 799 C>T (rs11225395) is associated with a higher risk of implant osseointegration failure (OR=3.07, 95% CI=2.02-4.67). The MMP-1 g. 3’ UTR C>T (rs5854) is associated with a higher risk of implant failure only in the Caucasian population (OR=6.88, 95% CI=3.48-13.59) while in the Asian population is a protective factor (OR=0.35, 95% CI=0.17-0.74). Finally, the MMP-3 g.-1612 5A>6A (rs3025058) and MMP-1 g.-519 A>G (rs1144393) showed no association with osseointegration failure. Conclusion: Even considering the limitations, our study suggests that some polymorphisms of metalloproteinases can be involved in the risk of osseointegration failure.
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 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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.024 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".