Table 1. Equations to predict glomerular filtration rate.
Name | Year | Gender | Scr | Scys | Equation |
C-MDRD | 2006 | 175×Scr−1.234×age−0.179(×0.79,if female) | |||
MacIsaac | 2006 | (86.7/Scys)-4.2 | |||
Ma | 2007 | 169×Scr−0.608×Scys−0.63×age−0.157(×0.83,if female) | |||
CKD-EPI2009Scr | 2009 | female | ≤0.7 | 144× (Scr/0.7)−0.329×0.993age(×1.159,if black) | |
>0.7 | 144× (Scr/0.7)−1.209×0.993age(×1.159,if black) | ||||
male | ≤0.9 | 141× (Scr/0.9)−0.411×0.993age(×1.159,if black) | |||
>0.9 | 141× (Scr/0.9)−1.209×0.993age(×1.159,if black) | ||||
CKD-EPI2012cys | 2012 | female | ≤0.8 | 133× (Scys/0.8)−0.499×0.996age×0.932 | |
>0.8 | 133× (Scys/0.8)−1.328×0.996age×0.932 | ||||
male | ≤0.8 | 133× (Scys/0.8)−0.499×0.996age | |||
>0.8 | 133× (Scys/0.8)−1.328×0.996age | ||||
CKD-EPI2012Scr-cys | 2012 | female | ≤0.7 | ≤0.8 | 130× (Scr/0.7)−0.248× (Scys/0.8)−0.375×0.995age(×1.08,if black) |
>0.8 | 130× (Scr/0.7)−0.248× (Scys/0.8)−0.711×0.995age(×1.08,if black) | ||||
>0.7 | ≤0.8 | 130× (Scr/0.7)−0.601× (Scys/0.8)−0.375×0.995age(×1.08,if black) | |||
>0.8 | 130× (Scr/0.7)−0.601× (Scys/0.8)−0.711×0.995age(×1.08,if black) | ||||
male | ≤0.9 | ≤0.8 | 135× (Scr/0.9)−0.207× (Scys/0.8)−0.375×0.995age(×1.08,if black) | ||
>0.8 | 135× (Scr/0.9)−0.207× (Scys/0.8)−0.711×0.995age(×1.08,if black) | ||||
>0.9 | ≤0.8 | 135× (Scr/0.9)−0.601× (Scys/0.8)−0.375×0.995age(×1.08,if black) | |||
>0.8 | 135× (Scr/0.9)−0.601× (Scys/0.8)−0.711×0.995age(×1.08,if black) |
Note: Scr was shown as mg/dL; Scys was shown as mg/L; age was shown as years.
Abbreviations: Scr: serum creatinine; Scys: serum cystatin C; C-MDRD: the Chinese modified Modification of Diet in Renal Disease equation; CKD-EPI: Chronic Kidney Disease Epidemiology Collaboration; CKD-EPI2009Scr: serum creatinine–based CKD-EPI equation which was developed in 2009; CKD-EPI2012cys: cystatin C–based CKD-EPI equation which was newly developed in 2012; CKD-EPI2012Scr-cys: serum creatinine– and cystatin C–based CKD-EPI equation which was newly developed in 2012.