Chronic Kidney Disease, Cardiovascular Risk, and Response to Angiotensin-Converting Enzyme Inhibition After Myocardial Infarction
Bibliographic record
Abstract
BACKGROUND: Persons with end-stage renal disease and those with lesser degrees of chronic kidney disease (CKD) have an increased risk of death after myocardial infarction (MI) that is not fully explained by associated comorbidities. Future cardiovascular event rates and the relative response to therapy in persons with mild to moderate CKD are not well characterized. METHODS AND RESULTS: We calculated the estimated glomerular filtration rate (eGFR) using the 4-variable Modification of Diet in Renal Disease method in 2183 Survival And Ventricular Enlargement (SAVE) trial subjects. SAVE randomized post-MI subjects (3 to 16 days after MI) with left ventricular ejection fraction < or =40% and serum creatinine <2.5 mg/dL to captopril or placebo. Cox proportional hazards models were used to evaluate the relative hazard rates for death and cardiovascular events associated with reduced eGFR. Subjects with reduced eGFR were older and had more extensive comorbidities. The multivariable adjusted risk ratio for total mortality associated with reduced eGFR from 60 to 74, 45 to 59, and <45 mL x min(-1) x 1.73 m(-2) (compared with eGFR > or =75 mL x min(-1) x 1.73 m(-2)) was 1.11 (0.86 to 1.42), 1.24 (0.96 to 1.60) and 1.81 (1.32 to 2.48), respectively (P for trend =0.001). Similar adjusted trends were present for CV mortality (P=0.001), recurrent MI (P=0.017), and the combined CV mortality and morbidity outcome (P=0.002). The absolute benefit of captopril tended to be greater in subjects with CKD: 12.4 versus 5.5 CV events prevented per 100 subjects with (n=719) and without (n=1464) CKD, respectively. CONCLUSIONS: CKD was associated with a heightened risk for all major CV events after MI, particularly among subjects with an estimated glomerular filtration rate <45 mL x min(-1) x 1.73 m(-2). Randomization to captopril resulted in a reduction of CV events irrespective of baseline kidney function.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".