Acute Decline in Renal Function, Inflammation, and Cardiovascular Risk after an Acute Coronary Syndrome
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Chronic kidney disease is associated with a higher risk of cardiovascular outcomes. The prognostic significance of worsening renal function has also been shown in various cohorts of cardiac disease; however, the predictors of worsening renal function and the contribution of inflammation remains to be established. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Worsening renal function was defined as a 25% or more decrease in estimated GFR (eGFR) over a 1-mo period in patients after a non-ST or ST elevation acute coronary syndromes participating in the Aggrastat-to-Zocor Trial; this occurred in 5% of the 3795 participants. RESULTS: A baseline C-reactive protein (CRP) in the fourth quartile was a significant predictor of developing worsening renal function (odds ratio, 2.48; 95% confidence interval, 1.49, 4.14). After adjusting for baseline CRP and eGFR, worsening renal function remained a strong multivariate predictor for the combined cardiovascular composite of CV death, recurrent myocardial infarction (MI), heart failure or stroke (hazard ratio, 1.6; 95% confidence interval, 1.1, 2.3). CONCLUSIONS: Patients with an early decline in renal function after an acute coronary syndrome are at a significant increased risk for recurrent cardiovascular events. CRP is an independent predictor for subsequent decline in renal function and reinforces the idea that inflammation may be related to the pathophysiology of progressive renal disease.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".