This study compared the prognostic value of equations used for the estimation of renal function in community population. We found that the Cockcroft–Gault equation was superior to the other three equations for predicting both all-cause mortality and cardiovascular or non-cardiovascular mortality. In addition, informants with Cockcroft–Gault derived eGFR < 80 mL/min per 1.73 m2 had a worse prognosis. Thus, the Cockcroft–Gault equation can serve as a risk-stratification tool for mortality in community population.
Scr is a waste product and continually generated via muscle metabolism. Normal-functioning kidneys filter out most of the Scr to maintain its levels within the normal range. Therefore, Scr is an important marker in the assessment of renal function (14). However, Scr is a late indicator and increases only following marked damage to the function of the nephrons. Therefore, this measure is not suitable for the identification of patients with early-stage kidney disease. A more favorable method for the assessment of function is the calculation of the eGFR, which is a non-invasive and inexpensive approach. Our results also confirm that eGFR is a stronger predictor of all-cause mortality and cardiovascular or non-cardiovascular mortality than Scr. CKD-EPI is currently used as the preferred method for GFR estimation in routine clinical practice due to its validity and accuracy (7, 15).
What is even more remarkable, however, is that many studies have confirmed that different equations have different values for predicting long-term adverse events in various populations. Rivera-Caravaca JM (16) analyzed 1,699 acute acute coronary syndrome patients and demonstrated that calculation of the eGFR using the Cockcroft–Gault equation presented higher predictive ability than the MDRD and CKD-EPI equations. Nevertheless, in patients with type 2 diabetes, the MDRD equation is superior in detecting impaired renal function compared with CKD-EPI and Cockcroft–Gault equations (17). Moreover, few studies have included individuals from the communities. Tariq Shafi and colleges (18) examined the association between eGFR and mortality among 16,010 participants and found that CKD-EPI categories improve mortality risk stratification compare with MDRD categories also use data from NHANES. However, it was difficult to reach a consensus based on the different sample size, and the Cockcroft–Gault equation was not examined in their study. Therefore, in this study, we expanded the sample size and also found that the predictive value of CKD-EPI formula was better than that of MDRD, but both significantly lower than that of Cockcroft–Gault equation, whether in all-cause mortality, cardiovascular or non-cardiovascular mortality.
The Cockcroft–Gault equation was proposed by Cockcroft and Gault in 1976 was developed in a Caucasian male population of 236 patients aged 18–92 years in order to predict creatinine clearance (and not GFR) in situations in which renal function was only slightly impaired (19). This original Cockcroft-Gault formula was found to be inaccurate for GFR prediction. Sheila M. Wilhelm and colleges (20) conducted a meta-analysis of 13 English-language trials comparing 24-hour measured creatinine clearance with Cockcroft-Gault estimated creatinine clearance by using various body weights or rounded Scr values and found that using the Cockcroft-Gault equation with no body weight and actual Scr value most closely estimated measured creatinine clearance. Our study also found that Cockcroft-Gault equation with no body weight is simpler and easier to obtain, and has higher predictive value for the long-term prognosis assessment of the general population in the United States, and thus more suitable for community promotion.
In conclusion, the present study, using a national large registry data, was conducted to further determine the optimal prediction equation for individuals in the community population. We found that the Cockcroft–Gault equation to estimate eGFR performed well in predicting all-cause mortality and cardiovascular or non-cardiovascular mortality. We speculated that this equation could accurately estimate GFR, and be simpler and identify more individuals with renal insufficiency, and thus, have higher predictive ability for the occurrence of adverse events.
The present study was characterized by several limitations. Firstly, the enrolled population was obtained from a representative survey, and some baseline variables such as previous disease history and history of taking medication were self-reported, which may be some recall errors. Secondly, the GFR measurement was not performed. For this reason, the predictive value of the true renal function was unknown. Therefore, all examined equations of the eGFR in our study were based on Scr. However, the measurement of the Scr-based eGFR is widely used in clinical practice. Finally, Scr was only measured once at baseline, which may not truly reflect the participant’s renal function status.