We have located links that may give you full text access.
Comparative Study
Journal Article
Validation Studies
Validation of the Virga GFR equation in a renal transplant population.
BACKGROUND: Virga and colleagues derived a glomerular filtration rate (GFR) equation which demonstrated a superior performance over Cockcroft-Gault (C-G) and modified diet in renal disease-isotope dilution mass spectrometry (MDRD-IDMS) formulas in chronic kidney disease (CKD) patients.
AIM: To validate the performance of the Virga equation on 103 renal transplant patients.
METHODS: We compared the performances of the MDRD-IDMS, C-G and Virga equations using inulin clearance as a reference test. Error, accuracy, relative accuracy, precision, scatter, and coefficient of variance of each equation were tested.
RESULTS: The mean absolute percentage error in estimated GFR by the new equation was 39.8 +/- 36.34% (mean +/- SD). Relative accuracy at 10, 30 and 50% range were 18.44, 48.54 and 73.78%, respectively. It has a bias of 0.09 +/- 0.169 and a precision of 19.69. Inulin clearance (GFR) in stages 1-4 were 106.19 +/- 14.11, 71.17 +/- 7, 42.37 +/- 8.40 and 22.92 +/- 3.48 ml/min/1.73 m(2), respectively. Comparative statistics in the overall population and in patients with transplant CKD stage 3T showed that the MDRD-IDMS equation had better accuracy. The performance of MDRD-IDMS over the Virga equation was clearly superior for males. In patients with CKD stage 2T, the Virga equation showed superiority over MDRD-IDMS. In the overall and subpopulations, the Virga equation performed better than the C-G equation.
CONCLUSION: Among renal transplant patients, the results suggest that the best GFR estimate is probably obtained using the MDRD-IDMS equation in moderate kidney failure whilst the Virga formula was superior to MDRD-IDMS for patients with mild kidney failure. As in untransplanted patients, estimating GFR with the MDRD-IDMS equation is not advisable in the range of normal renal function because of its known underestimation of renal function.
AIM: To validate the performance of the Virga equation on 103 renal transplant patients.
METHODS: We compared the performances of the MDRD-IDMS, C-G and Virga equations using inulin clearance as a reference test. Error, accuracy, relative accuracy, precision, scatter, and coefficient of variance of each equation were tested.
RESULTS: The mean absolute percentage error in estimated GFR by the new equation was 39.8 +/- 36.34% (mean +/- SD). Relative accuracy at 10, 30 and 50% range were 18.44, 48.54 and 73.78%, respectively. It has a bias of 0.09 +/- 0.169 and a precision of 19.69. Inulin clearance (GFR) in stages 1-4 were 106.19 +/- 14.11, 71.17 +/- 7, 42.37 +/- 8.40 and 22.92 +/- 3.48 ml/min/1.73 m(2), respectively. Comparative statistics in the overall population and in patients with transplant CKD stage 3T showed that the MDRD-IDMS equation had better accuracy. The performance of MDRD-IDMS over the Virga equation was clearly superior for males. In patients with CKD stage 2T, the Virga equation showed superiority over MDRD-IDMS. In the overall and subpopulations, the Virga equation performed better than the C-G equation.
CONCLUSION: Among renal transplant patients, the results suggest that the best GFR estimate is probably obtained using the MDRD-IDMS equation in moderate kidney failure whilst the Virga formula was superior to MDRD-IDMS for patients with mild kidney failure. As in untransplanted patients, estimating GFR with the MDRD-IDMS equation is not advisable in the range of normal renal function because of its known underestimation of renal function.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app