Effect of rs4646994 polymorphism of angiotensin-converting enzyme on the risk of nonischemic cardiomyopathy
Bibliographic record
Abstract
BACKGROUND: Angiotensin-converting enzyme (ACE) gene polymorphisms have recently been shown to be associated with risk of developing left ventricular hypertrophy (LVH). However, the results were controversial. We aimed to conduct this meta-analysis to further confirm the association between ACE rs4646994 polymorphism and hypertrophic cardiomyopathy (HCM)/dilated cardiomyopathy (DCM). METHODS: PubMed, Embase, the Chinese National Knowledge Information, and Wanfang databases were searched for eligible studies. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of included studies. Then we evaluated the association between ACE gene mutation and HCM/DCM by calculating odds ratios (ORs) and 95% confidence intervals (95% CIs). Subgroup analysis was further performed to explore situations in specialized subjects. Sensitivity analysis and publication bias was assessed to confirm the study reliability. RESULTS: There were 13 studies on DCM (2004 cases and 1376 controls) and 16 studies on HCM (2161 controls and 1192 patients). ACE rs4646994 polymorphism was significantly associated with DCM in all genetic models. However, in HCM, four genetic models (allele model, homozygous model, heterozygous model, and dominant model) showed significant association between ACE rs4646994 polymorphism and DCM. In subgroup analysis, we found that ACE rs4646994 polymorphism was significantly associated with DCM/HCM in Asian population. Finally, we also conducted a cumulative meta-analysis, which indicates that the results of our meta-analysis are highly reliable. CONCLUSION: ACE rs4646994 polymorphism increases the risk of DCM/HCM in Asians, but not in Caucasians. More case-control studies are needed to strengthen our conclusions and to assess the gene-gene and gene-environment interactions between ACE rs4646994 polymorphism and DCM/HCM.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.029 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".