| Literature DB >> 30430784 |
Sholhui Park1, Tae Dong Jeong2.
Abstract
The creatinine-based Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation can be calculated according to race, sex, and creatinine concentration (subgroup equation) or in the form expressed by one equation (single equation). Minor differences in the constants used in the CKD-EPI equations (subgroup vs single equations) could result in a significant difference in the estimated glomerular filtration rate (eGFR). We evaluated the impact of this difference in 79,709 Korean patients. The eGFR was calculated as an integer using the single and subgroup CKD-EPI equations. The differences in eGFR and GFR categories between the equations were analyzed. eGFR was higher in the subgroup equation than the single equation by 1 mL/min/1.73 m² for 12,476 (27.4%) Korean females. The GFR category based on the subgroup equation was reclassified using the single equation for 352 (0.77%) females. Based on the results, the constant of the single equation was optimized. There was no difference in eGFR values between equations using a multiplier of 1.0213 instead of 1.018 for the "white or other" females constant in the single CKD-EPI equation. Clinicians should carefully apply the CKD-EPI equation because eGFR values may differ by 1 mL/min/1.73 m² depending on the manner of calculation. To minimize these differences, the constants of the single equation should be revised. © The Korean Society for Laboratory Medicine.Entities:
Keywords: Constant modification; Creatinine-based Chronic Kidney Disease Epidemiology Collaboration equation; Glomerular filtration rate
Mesh:
Substances:
Year: 2019 PMID: 30430784 PMCID: PMC6240521 DOI: 10.3343/alm.2019.39.2.205
Source DB: PubMed Journal: Ann Lab Med ISSN: 2234-3806 Impact factor: 3.464
Clinical characteristics of study patients
| Variable | Female (N = 45,560) | Male (N = 34,149) | Total (N = 79,709) |
|---|---|---|---|
| Age (yr)* | 51 (26) | 53 (24) | 52 (25) |
| Age categories, N (%) | |||
| < 40 | 12,614 (28) | 8,024 (23) | 20,638 (26) |
| 41–49 | 8,844 (19) | 6,504 (19) | 15,348 (19) |
| 50–59 | 9,372 (21) | 7,682 (22) | 17,054 (21) |
| 60–69 | 6,858 (15) | 6,309 (18) | 13,167 (17) |
| 70–79 | 4,864 (11) | 3,973 (12) | 8,837 (11) |
| ≥ 80 | 3,008 (7) | 1,657 (5) | 4,665 (6) |
| Serum creatinine (µmol/L)* | 70 (13) | 91 (18) | 78 (24) |
| Serum creatinine (mg/dL)* | 0.79 (0.15) | 1.03 (0.20) | 0.88 (0.27) |
| eGFRsingle CDK-EPI (mL/min/1.73 m2)* | 87 (26) | 84 (24) | 86 (25) |
| eGFRsingle CDK-EPI (mL/min/1.73 m2) categories, N (%) | |||
| G1, ≥ 90 | 20,716 (45) | 12,676 (37) | 33,392 (42) |
| G2, 60–89 | 20,300 (45) | 17,295 (51) | 37,595 (47) |
| G3a, 45–59 | 2,584 (6) | 2,411 (7) | 4,995 (6) |
| G3b, 30–44 | 1,105 (2) | 960 (3) | 2,065 (3) |
| G4, 15–29 | 485 (1) | 403 (1) | 888 (1) |
| G5, < 15 | 370 (1) | 404 (1) | 774 (1) |
*median (interquartile range).
Abbreviations: CKD-EPI, Chronic Kidney Disease Epidemiology Collaboration; eGFR, estimated glomerular filtration rate.
Fig. 1Distribution of GFR category according to the creatinine-based CKD-EPI equation in females. The overall agreement between the subgroup and single equations was 99.2% (weighted kappa, 0.990; 95% confidence interval, 0.989–0.991). (A) When using the single equation with the constant 1.018, the GFR categories of 352 (0.77%, 352/45,560) patients were reclassified. (B) The use of 1.0213 rather than 1.018 eliminated the difference in eGFR. *GFR=141×min (Scr/κ, 1)α×max (Scr/κ, 1)−1.209×(0.993)Age×1.018 [if female]×1.159 [if black]; †GFR=141×min (Scr/κ, 1)α×max (Scr/κ, 1)−1.209×(0.993)Age×1.0213 [if female]×1.159 [if black].
Abbreviations: CKD-EPI, Chronic Kidney Disease Epidemiology Collaboration; eGFR, estimated glomerular filtration rate; G1, ≥90; G2, 60–89; G3a, 45–59; G3b, 30–44; G4, 15–29; G5,<15 mL/min/1.73 m2; GFR, glomerular filtration rate.