AGTR1rs5186 Polymorphism Is Associated with the Risk of Restenosis after Percutaneous Coronary Intervention: A Meta-Analysis
Bibliographic record
Abstract
Background: Progress has been made in genetic investigations on restenosis for the past 20 years, many studies regarding AGTR1 rs5186 polymorphism and restenosis after percutaneous coronary intervention (PCI) have been published, but the result remains controversial. The study aimed to explore the relationship between rs5186 polymorphism and the risk of restenosis after PCI. Methods: We performed a systematic search on PubMed, Web of Science, Embase, CNKI, and Wan Fang databases up to December 2021. Two authors individually extracted all useful data of each study involved in this meta-analysis and assessed the study quality using the Newcastle-Ottawa scale. Odds ratios (ORs) and 95% confidence intervals (CIs) were combined in different genetic models for evaluation using a random-effects model or fixed-effect model. Results: There were eventually 8 studies of 1111 cases and 4097 controls eligible for this meta-analysis. Significant associations were found between rs5186 polymorphism and restenosis after PCI.allelic (OR: 1.31, 95% CI: 1.17−1.47, p < 0.001), homozygous (OR: 1.90, 95% CI: 1.50−2.44, p < 0.001), heterozygous (OR: 1.10, 95% CI: 0.93−1.29, p = 0.27), recessive (OR: 1.80, 95% CI: 1.37−2.36, p < 0.001), dominant genetic model (OR: 1.24, 95% CI: 1.06−1.44, p = 0.006). Subgroup analyses indicated a significant association in Asians. Conclusions: The rs5186 polymorphism in the AGTR1 gene increases the risk of restenosis after PCI in Asians significantly.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.061 |
| Bibliometrics | 0.006 | 0.007 |
| 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) | 0.003 | 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".