Fasting Plasma Glucose Predicts Survival And Angiographic Progression in High-Risk Postmenopausal Women with Coronary Artery Disease
Bibliographic record
Abstract
BACKGROUND: We studied the association of baseline fasting plasma glucose (FPG) levels with survival and coronary artery disease (CAD) progression among postmenopausal women without unstable angina. METHODS: Women were recruited from seven centers in the Women's Angiographic Vitamin and Estrogen Trial (WAVE) (n = 423). Event follow-up was available for 400 women (65.1 +/- 8.5 years, 66% white, 92% hypertensive, 19% smokers, 67% hypercholesterolemic). Thirty-eight percent of the women had diabetes or FPG > 125 mg/dL, and 21% had a fasting glucose 100-125 mg/dL. Follow-up angiography was performed in 304 women. Cox regression was used to model survival from a composite outcome of death or myocardial infarction (D/MI, 26 events; median follow-up 2.4 years). Angiographic progression was analyzed quantitatively using linear regression accounting for baseline minimum lumen diameter (MLD), follow-up time, and intrasubject correlations using generalized estimating equations. Regression analyses were adjusted for follow-up time, baseline age, treatment assignment, and Framingham risk (excluding diabetes). RESULTS: Women with impaired fasting glucose/diabetes mellitus (IFG/DM) had a relative risk (RR) of D/MI of 4.2 ( p = 0.009). In all women, each 10 mg/dL increase in FPG was associated with an 11% increase ( p < 0.001) in the hazard of D/MI. Each 10 mg/dL increase in FPG was associated with a 6.8 mum decrease in MLD over the follow-up period ( p = 0.005). CONCLUSIONS: Higher FPG is associated with increased risk of D/MI and greater narrowing of the coronary lumen in women with CAD. Aggressive monitoring of glucose levels may be beneficial for secondary CAD prevention.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".