Enter the creatinine level, age, gender, and race into the calculator to determine the Mdrd score.

Mdrd Formula

The following formula is used to calculate the Mdrd (Modification of Diet in Renal Disease) score. Mdrd = 186 * (Creatinine/88.4)^-1.154 * (Age)^-0.203 * (0.742 if female) * (1.210 if African American)Variables:

  • Mdrd is the estimated glomerular filtration rate (eGFR) in mL/min/1.73m^2 Creatinine is the serum creatinine level in µmol/L Age is the patient’s age in years The last two factors account for gender and race respectively

To calculate the Mdrd score, multiply 186 by the creatinine level (converted to mg/dL by dividing by 88.4) raised to the power of -1.154. Multiply this result by the patient’s age raised to the power of -0.203. If the patient is female, multiply the result by 0.742. If the patient is African American, multiply the result by 1.210.

What is a Mdrd?

The MDRD (Modification of Diet in Renal Disease) is a formula used by healthcare professionals to estimate the glomerular filtration rate (GFR) of a patient, which is a measure of kidney function. The MDRD takes into account the patient’s age, gender, race, and serum creatinine level. This formula is particularly useful in detecting early kidney disease and determining its stage in patients.

How to Calculate Mdrd?

The following steps outline how to calculate the Mdrd using the given formula:

  1. First, determine the serum creatinine level (Creatinine) in µmol/L.
  2. Next, determine the patient’s age (Age) in years.
  3. Next, determine the patient’s gender (Gender). Assign a value of 0.742 if female or 1 if male.
  4. Next, determine the patient’s race (Race). Assign a value of 1.210 if African American or 1 if not African American.
  5. Finally, calculate the Mdrd using the formula: Mdrd = 186 * (Creatinine/88.4)^-1.154 * (Age)^-0.203 * (Gender) * (Race).

Example Problem:

Use the following variables as an example problem to test your knowledge:

Serum creatinine level (Creatinine) = 100 µmol/L

Patient’s age (Age) = 60 years

Patient’s gender (Gender) = 0.742 (female)

Patient’s race (Race) = 1 (not African American)