1. In this meta-analysis, estimated glomerular filtration rate (eGFR) and albumin-to-creatinine ratio (ACR) were shown to enhance predictive value when added to traditional risk factor information.
2. Combined eGFR and ACR data were shown to have greater predictive value for cardiovascular risk than any traditional modifiable risk factors such as systolic blood pressure, smoking status, or cholesterol levels.
Evidence Rating Level: 1 (Excellent)
Study Rundown: Chronic kidney disease has been shown to be a risk factor for cardiovascular disease and subsequent mortality. Two measurements that have been used to predict the risk of cardiovascular disease are the estimated glomerular filtration rate (eGFR) and the presence of albuminuria. The data regarding the predictive value of these measurements is; however, conflicting. The authors of this study undertook the task of determining the predictive value of adding eGFR and albumin-to-creatinine ratio (ACR) to the traditional risk factors for cardiovascular disease. They found that eGFR and ACR lend great predictive value when examined with traditional cardiovascular risk factors such as age, sex, systolic blood pressure, and cholesterol levels. Additionally, it was shown that the combination of eGFR and ACR were better at identifying cardiovascular risk than any traditional modifiable risk factor alone.
This study benefits from the large patient population used to generate the conclusions. The meta-analysis approach allows for a strong argument that eGFR and albuminuria have strong predictive value when considering all of the current available data. This study is however, not without its limitations; there were measurement inconsistencies among the studies used in the meta-analysis, such as the methods to derive creatinine and albuminuria data. Furthermore, sub-population differences were present in that the majority of black patients in the study were from the United States and Asian patients were more likely to have albuminuria determined by dipstick.
The study was funded by the US National Kidney Foundation, National Institute of Diabetes and Digestive and Kidney Diseases.
In-Depth [meta-analysis]: This study examined 637,315 individuals gathered from 24 cohorts from the Chronic Kidney disease Prognosis Consortium. C statistic differences for cardiovascular mortality were determined for models consisting of traditional risk factors with and without eGFR and ACR, as a measure of predictive power.
It was found that eGFR and ACR enhanced the predictive value for cardiovascular mortality over traditional risk factor assessment (C statistic difference 0.0139 [95% CI 0.0105 – 0.0174] for ACR or dipstick, 0.0065 [95% CI 0.0042 – 0.0088] for eGFR, and 0.0167 [95% CI 0.0131 – 0.0202] for eGFR and ACR or dipstick). In addition, eGFR and ACR combined showed a greater risk discrimination than the majority of solitary traditional predictors (C statistic dropped by 0.0227 [0.0158 – 0.0296] with elimination of eGFR and ACR while single predictors decreased less than 0.007).
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