Glutathione Peroxidase 1 Activity and Cardiovascular Events in Patients with Coronary Artery Disease
Bibliographic record
Abstract
BACKGROUND: Cellular antioxidant enzymes such as glutathione peroxidase 1 and superoxide dismutase have a central role in the control of reactive oxygen species. In vitro data and studies in animal models suggest that these enzymes may protect against atherosclerosis, but little is known about their relevance to human disease. METHODS: We conducted a prospective study among 636 patients with suspected coronary artery disease, with a median follow-up period of 4.7 years (maximum, 5.4) to assess the risk of cardiovascular events associated with base-line erythrocyte glutathione peroxidase 1 and superoxide dismutase activity. RESULTS: Glutathione peroxidase 1 activity was among the strongest univariate predictors of the risk of cardiovascular events, whereas superoxide dismutase activity had no association with risk. The risk of cardiovascular events was inversely associated with increasing quartiles of glutathione peroxidase 1 activity (P for trend <0.001); patients in the highest quartile of glutathione peroxidase 1 activity had a hazard ratio of 0.29 (95 percent confidence interval, 0.15 to 0.58; P<0.001), as compared with those in the lowest quartile. Glutathione peroxidase 1 activity was affected by sex and smoking status but retained its predictive power in these subgroups. After adjustment for these and other cardiovascular risk factors, the inverse association between glutathione peroxidase 1 activity and cardiovascular events remained nearly unchanged. CONCLUSIONS: In patients with coronary artery disease, a low level of activity of red-cell glutathione peroxidase 1 is independently associated with an increased risk of cardiovascular events. Glutathione peroxidase 1 activity may have prognostic value in addition to that of traditional risk factors. Furthermore, increasing glutathione peroxidase 1 activity might lower the risk of cardiovascular events.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".