Novel Algorithm for Mealtime Insulin Dose Estimation ID'd
Food insulin index improves acute postprandial glycemia in type 1 diabetes versus carb counting
TURSDAY, Oct. 4 (HealthDay News) -- In patients with type 1 diabetes using intensive insulin pump therapy, a novel food insulin index (FII)-based algorithm improves acute postprandial glycemia compared with the use of carbohydrate counting, according to a study published in the October issue of Diabetes Care.
Jiansong Bao, from the University of Sydney in Australia, and colleagues compared a new FII-based algorithm for estimating mealtime insulin dose with the use of carbohydrate counting in 28 adults with type 1 diabetes who used insulin pump therapy. Two breakfast meals that differed approximately two-fold in carbohydrate content, and that compared equally in terms of energy, glycemic index, fiber, and calculated insulin demand, were consumed by participants in random order on three consecutive mornings. For one meal, the bolus insulin dose was determined by applying carbohydrate counting (75 g carbohydrate). For the other two mornings, carbohydrate counting and the FII algorithm were applied to a meal containing 41 g carbohydrate. The three-hour postprandial glycemia was assessed using a real-time continuous glucose monitor.
The investigators found that, compared to carbohydrate counting, the FII algorithm significantly decreased the peak glucose excursion and the glucose incremental area under the curve over three hours. The percentage of time within the normal blood glucose range improved significantly with the FII algorithm. The occurrence of hypoglycemia did not differ significantly between the groups.
"An insulin algorithm based on physiological insulin demand evoked by foods in healthy subjects may be a useful tool for estimating mealtime insulin dose in patients with type 1 diabetes," the authors write.