Estimated renal function and cardiovascular or non-cardiovascular mortality in community population: results from the national health and nutrition examination surveys

Abstract Background Renal insufficiency is an important risk factor for mortality in various populations. The present study was conducted to determine the optimal equation for the estimation of renal function in predicting adverse events in community population in US. Methods We examined the Cockcroft–Gault, modification of diet in renal disease (MDRD), Mayo Healthy-Chronic Kidney Disease (Mayo), and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) derived estimated glomerular filtration rates (eGFR) and the association with cardiovascular or non-cardiovascular mortality among 25,677 participants of US National Health and Nutrition Examination Survey from 2005 to 2014. Results The cardiovascular mortality and non-cardiovascular mortality increased with decrease in renal function. The MDRD derived eGFR exhibited the lowest predictive ability for all-cause mortality in all participants. For cardiovascular mortality, the Cockcroft–Gault derived eGFR exhibited the highest predictive power compared with the MDRD (area under the curve [AUC]: 0.842 vs. 0.764, p < 0.001), Mayo (AUC: 0.842 vs. 0.812, p < 0.001) and CKD-EPI (AUC: 0.842 vs. 0.813, p < 0.001) derived eGFR. For non-cardiovascular mortality, the Cockcroft–Gault derived eGFR exhibited similar superiority in non-cardiovascular mortality. Conclusions The value of the Cockcroft–Gault equation was superior to the other three equations for the prediction of cardiovascular or non-cardiovascular mortality in community population. This equation can serve as a risk-stratification tool for long-term events in community population.