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MDRD GFR Equation

Calculators  Renal
MDRD GFR Equation is quick and practical tool utilized for the estimation of glomerular filtration rate
Sex
Female 0.742
Male 1
Black race
No 1
Yes 1.212
Age
y
Serum Creatinine level
m
Result:

Background

Measured Factor
Glomerular filtration rate
Measured Factor Disease
  • Chronic kidney disease
Measured Factor Detail
MDRD GFR Equation is used to estimate the glomerular filtration rate in patients of chronic kidney disease. The calculation takes into account patient features such as level of creatinine, gender, black race and age of patient.
Speciality
Renal Pathologist
Body System
Renal
Formula
GFR = 186 × Serum Cr-1.154 × age-0.203 × 1.212 (if patient is black) × 0.742 (if female)
Measured Factor Low Impact
  • Value <0.7 mg/DL indicates low concentration and risk
Measured Factor High Impact
  • Value >2.5 mg/DL illustrates high concentration and risk

Result Interpretation

Ranges Ranges
  • Critical Low: <0.7
  • Critical High: >2.5
  • Normal: 0.7-1.4
  • Normal Adult Male: 0.7-1.4
  • Normal Adult Female: 0.7-1.4
  • Normal Pediatric: 0.7-1.4
  • Normal Geriatric Male: 0.7-1.4
  • Normal Geriatric Female: 0.7-1.4
Result High Conditions
  • Chronic kidney disease
Test Limitations
The MDRD equation had poor accuracy and precision with Chinese patients with type-2 diabetes to the estimation of GDR. According to Lui X et al. there is a need for a better equation for estimation of GFR in the Asiatic population.
References: 2

Studies

Study Validation 1
A study was conducted in 1628 chronic renal disease patients to validate Modification of Diet in Renal Disease (MDRD) to estimate glomerular filtration rate (GFR). Randomly 1070 patients selected in the training sample and 558 patients as a validation sample. Lower GFR is independent on older age, higher serum creatinine concentration, female sex, higher serum urea nitrogen levels, non-black ethnicity, and lower serum albumin levels with p < 0.001. 19% overestimated GFR with measured creatinine clearance and 16% with the Cockcroft-Gault formula. 86.6% variance of GFR logarithm from measured creatinine clearance and 84.2% variance of GFR logarithm from the Cockcroft-Gault formula after adjustment of overestimation. In conclusion, the study indicates more accuracy of GFR from MDRD.
References: 1
Study Validation 2
A validation study was conducted in 1628 chronic renal disease patients with 4-variable Modification of Diet in Renal Disease (MDRD) to estimate glomerular filtration rate (GFR) by comparing with 6-variable MDRD and Cockcroft-Gault equations. According to Levey AS et al. results mean GFR was 39.8 mL/min per 1.73 m^2 with SD 21.2. Revised 4-variable equation had better accuracy and precision with 90% and original 6-variable equation had 91%, the Cockcroft-Gault equation had 60%, and bias corrected latter had 83% within 30% GFR. In conclusion, the study indicates more accuracy and precision of GFR from 4-variable MDRD than other equations.
References: 3
Study Additional 1
A study was conducted in 7001 participants to compare prevalence based on the population with Modification of Diet in Renal Disease (MDRD), the Full Age Spectrum creatinine equation (FAScre), the revised Lund-Malmo equation (LM), and the Chronic Kidney Disease Epidemiology Collaboration equations with cystatin c (CKD-EPIcys), with creatinine (CKD-EPIcre) and with creatinine and cystatin C (CKD-EPIcrecys) to estimate glomerular filtration rate (GFR). Estimated prevalence were 6.9% FAScre, 6% LM, 5% MDRD, 3.8% CKD-EPIcre, 2.3% CKD-EPIcrecys, and 2.1% CKD-EPIcys of decreased kidney function.There were smaller systemic differences between equations comparing with serum creatinine alone or serum cystatin C and increased by increasing GFR. In addition, the study indicates that the estimation of the prevalence of decreased kidney function based on the equation used.
References: 4
Study Additional 2
Population-based studies were conducted in chronic renal disease patients to estimate glomerular filtration rate (GFR) by comparing with Modification of Diet in Renal Disease (MDRD), the Mayo equation and Cockcroft-Gault (CG) equations. According to Shankar A et al. results prevalence of chronic kidney disease was 4.8% from Mayo equation, 16.5% from CG equation and 17.2% from MDRD equation. The CG and MDRD equations showed >10% false positive rate. In addition, the study found that the MDRD and CG equations had more accuracy and precision to estimate GFR.
References: 5
Study Additional 3
A study was conducted in Chinese patients with type-2 diabetes disease to estimate glomerular filtration rate (GFR) with Modification of Diet in Renal Disease (MDRD) equation. According to Liu X et al. results from 209 patients that 92.9 mL/min per 1.73 m2 precision with MDRD equation was best as compared with the Chinese equation 1 and 2. The Chinese equation 2 had greater accuracies with p < 0.05. In conclusion, the study found that need of a better equation more accuracy and precision to estimate GFR in the Chinese patients with type-2 diabetes.
References: 2

References

  1. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med. 1999;130(6):461-70.
  2. Liu X, Qiu X, Shi C, Huang H, Huang J, Li M, et al. Modified glomerular filtration rate-estimating equations developed in asiatic population for chinese patients with type 2 diabetes. Int J Endocrinol. 2014;2014:521071.
  3. Levey AS, Coresh J, Greene T, Stevens LA, Zhang YL, Hendriksen S, et al. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med. 2006;145(4):247-54.
  4. Trocchi P, Girndt M, Scheidt-nave C, Markau S, Stang A. Impact of the estimation equation for GFR on population-based prevalence estimates of kidney dysfunction. BMC Nephrol. 2017;18(1):341.
  5. Shankar A, Lee KE, Klein BE, Muntner P, Brazy PC, Cruickshanks KJ, et al. Estimating glomerular filtration rate in a population-based study. Vasc Health Risk Manag. 2010;6:619-27.