Key result
The Cockcroft-Gault equation exhibited the highest predictive power for cardiovascular mortality compared with the MDRD, Mayo, and CKD-EPI equations (AUC 0.842 vs 0.764, 0.812, and 0.813, respectively; p<0.001).
Why the study?
Renal insufficiency is a key mortality risk factor, but the optimal equation to estimate renal function for predicting adverse events in the US community population remained undetermined.
Does the Cockcroft-Gault equation provide better prediction of cardiovascular and non-cardiovascular mortality compared to MDRD, Mayo, and CKD-EPI equations in a general community population?
Cohort (n=25,677)
Yes
Does the Cockcroft-Gault equation provide better prediction of cardiovascular and non-cardiovascular mortality compared to MDRD, Mayo, and CKD-EPI equations in a general community population?
The Cockcroft-Gault equation demonstrated superior predictive ability for cardiovascular and non-cardiovascular mortality compared to MDRD, Mayo, and CKD-EPI equations in a large US community population.
Cockcroft-Gault may improve CV mortality prediction in community cohorts; hypothesis-generating and should not yet change eGFR equation selection.
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.
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Huang et al. (2021) conducted a cohort in General community population (n=25,677). Cockcroft-Gault derived eGFR vs. MDRD, Mayo, and CKD-EPI derived eGFR was evaluated on Predictive ability for cardiovascular mortality (Area Under the Curve) (AUC 0.842, p=<0.001). The Cockcroft-Gault equation exhibited the highest predictive power for cardiovascular mortality compared with the MDRD, Mayo, and CKD-EPI equations (AUC 0.842 vs 0.764, 0.812, and 0.813, respectively; p<0.001).
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