Improved diabetes control by using 'close adjustment algorithms'

Abstract

Background: Intensive insulin therapy increases the frequency of severe hypoglycemia despite markedly improved glycemic control in patients with type 1 diabetes mellitus. To determine the optimal dose of insulin, the authors designed algorithms based on self-monitored blood glucose levels.

Methods: Each dose of insulin was composed of two components: a basal dose determined on the basis of blood glucose levels over the previous two days and an additional dose determined on the basis of blood glucose level just before insulin injection. The patients were instructed to adjust each dose according to the algorithms. The authors investigated the effects of using algorithms on glycemic control, anthropometric data, body composition, and lipid profile in seven females with type 1 diabetes 12-20 years old.

Results: After 3 months, the daily dose of insulin increased significantly from 0.93 +/- 0.18 to 1.16 +/- 0.26 units/kg of body weight, and haemoglobin A(1C) decreased significantly from 8.27 +/- 1.33 to 6.50 +/- 0.64%. Severe hypoglycemia, however, did not occur. Body mass index increased significantly from 21.7 +/- 2.7 to 22.7 +/- 2.9 kg/m(2) with no increase in the percentage of body fat. All lipid-profile data showed a decreasing trend.

Conclusions: Algorithms developed on the basis of self-monitored blood glucose levels are useful in determining the optimal dose of insulin and can improve glycemic control and lipid metabolism.