How to Compute Mage Diabetes

The MAGE (Mean Amplitude of Glycemic Excursions) is a common measure of the volatility of blood glucose levels, an indication of the level of the level of control of diabetes. MAGE is typically used with continuous blood glucose monitoring systems, which provide blood glucose level readings every 10 seconds. However, there are published medical studies in which the MAGE algorithm is used with a much smaller set of data, typically seven to 10 readings per day over two days.

Things You'll Need

• Pencil
• Paper
• Continuous blood glucose monitor or standard blood glucose monitor and test strips
• Calculator with statistical functions or computer with spreadsheet software

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Instructions

Determine MAGE +/-

• 1

  Use a continuous blood glucose monitor, and record all readings over a 24-hour period. Alternatively, use a normal blood glucose meter and record at least 10 readings per day, spaced evenly apart, for two days.

• 2

  Calculate the standard deviation of all the blood glucose measurements taken. This is best accomplished with a computer and spreadsheet program, but may be performed with a calculator. See Resources for more information on calculating standard deviation.

• 3

  For each glucose reading, calculate the difference from the previous reading, and record this result. If the reading is higher than the previous reading, this will be a positive (+) change, and if the reading is lower than the previous, this will be a negative (-) change. When completed, you will have a difference result for every reading except the first.

• 4

  Compare each result calculated in Step 3 against the standard deviation calculated in Step 2. For this step, ignore the +/- signs and just consider the magnitude of the number. Discard from further consideration all data where the magnitude of the difference (Step 3) is less than the standard deviation.

• 5

  Calculate the arithmetic mean (average) of the differences (step 3) which were not eliminated from consideration in step 2. The mean is calculated by adding all the differences and dividing by the number of data points considered.