Cardiovascular Risk Prediction Better With eGFR, ACR

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Cardiovascular Risk Prediction Better With eGFR, ACR
Cardiovascular Risk Prediction Better With eGFR, ACR

(HealthDay News) — Estimated glomerular filtration rate (eGFR) and albumin-to-creatinine ratio (ACR) improve prediction of cardiovascular (CV) risk above traditional risk factors, according to a meta-analysis published in The Lancet Diabetes & Endocrinology

The research was published to coincide with the European Renal Association-European Dialysis and Transplant Association Congress, held from May 28 to 31 in London.

Kunihiro Matsushita, MD, from the Johns Hopkins Bloomberg School of Public Health in Baltimore, and colleagues used a meta-analysis approach to examine the addition of creatinine-based eGFR and albuminuria to traditional risk factors for prediction of CV risk. 

Data were included for 637,315 individuals without a history of cardiovascular disease (CVD) from 24 cohorts.

The researchers found that in general populations, the addition of eGFR and ACR significantly improved the discrimination of CV outcomes beyond traditional risk factors; the improvement was greater for ACR vs. eGFR, and was more evident for CV mortality and heart failure than for coronary disease and stroke. 

In individuals with diabetes or hypertension, the discrimination improvement with eGFR or ACR was especially pronounced; for patients without either of these disorders, the improvement with ACR remained significant for CV mortality and heart failure. 

The combination of eGFR and ACR outperformed most single traditional parameters for risk discrimination in individuals with chronic kidney disease; after omission of eGFR and ACR, the C-statistic for CV mortality decreased by 0.0227 vs. less than 0.007 for any single modifiable traditional predictor.

"Our results lend some support to also incorporating eGFR and ACR into assessments of cardiovascular risk in the general population," the researchers wrote.

Several authors disclosed financial ties to the pharmaceutical industry.

Reference

  1. Matsushita K et al. Lancet Diabetes Endocrinol. 2015;doi:10.1016/S2213-8587(15)00040-6.
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