Effects of Stenting for Atherosclerotic Renal Artery Stenosis on eGFR and Predictors of Clinical Events in the CORAL Trial
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Atherosclerotic renal artery stenosis may cause kidney function loss, but effects of stenting on eGFR and clinical events associated with CKD are uncertain. Our study objectives were to determine effects of stenting on eGFR and predictors of clinical events. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Participants (n=931) in the Cardiovascular Outcomes in Renal Artery Stenosis Trial (from May of 2005 to September of 2012) had >60% atherosclerotic renal artery stenosis and systolic hypertension on two or more antihypertensive drugs and/or stage ≥3 CKD. The intervention was stenting versus no stenting on a background of risk factor management: renin-angiotensin system inhibition, statin, antiplatelet therapy, and smoking cessation education. The effect of stenting on eGFR by the serum creatinine-cystatin C Chronic Kidney Disease Epidemiology Collaboration equation was the prespecified analysis of kidney function. Predictors of eGFR and CKD outcomes (≥30% eGFR loss, ESRD, and death) and cardiovascular disease outcomes (stroke, myocardial infarction, heart failure, and death) controlling for eGFR and albuminuria were also determined. RESULTS: eGFR was 59±24 ml/min per 1.73 m(2) (mean±SD) at baseline. Over 3 years, eGFR change, assessed by generalized estimating equations, was -1.5±7.0 ml/min per 1.73 m(2) per year in the stent group versus -2.3±6.3 ml/min per 1.73 m(2) per year in the medical therapy only group (P=0.18). eGFR predictors (multiple variable generalized estimating equations) were age, albuminuria, systolic BP, and diabetes (inverse associations) as well as men, total cholesterol, and HDL cholesterol (positive associations). CKD outcomes events occurred in 19% (175 of 931), and predictors (Cox proportional hazards models) included albuminuria (positive association), systolic BP (positive association), and HDL cholesterol (inverse association). Cardiovascular disease outcomes events occurred in 22% (207 of 931), and predictors included age, albuminuria, total cholesterol, prior cardiovascular disease, and bilateral atherosclerotic renal artery stenosis (positive associations). CONCLUSIONS: Stenting did not influence eGFR in participants with atherosclerotic renal artery stenosis receiving renin-angiotensin system inhibition-based therapy. Predictors of clinical events were traditional risk factors for CKD and cardiovascular 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".