A new mathematical model can predict with more than 90 per cent accuracy the blood glucose levels of individuals with type 1 diabetes up to 30 minutes in advance of imminent changes in their levels.
"Many people with type 1 diabetes use continuous glucose monitors, which examine the fluid underneath the skin," said Peter Molenaar from the Pennsylvania State University.
"But the glucose levels under the skin trail blood glucose levels from anywhere between 8 and 15 minutes. This is especially problematic during sleep. Patients may become hypoglycemic well before the glucose monitor alarm tells them they are hypoglycemic, and that could lead to death," said Molenaar.
According to Molenaar, a person's blood glucose levels fluctuate in response to his or her insulin dose, meal intake, physical activity and emotional state. How great these fluctuations are depends on the individual.
The researchers created a time-varying model estimated by the extended Kalman filtering technique.
This model accounts for time-varying changes in glucose kinetics due to insulin and meal intake.
The team tested the accuracy of its model with 30 virtual patients and five living patients with type 1 diabetes.
"We learned that the dynamic dependencies of blood glucose on insulin dose and meal intake vary substantially in time within each patient and between patients," said researcher Qian Wang.
"The high prediction fidelity of our model over 30-minute intervals allows for the execution of optimal control of fast-acting insulin dose in real time because the initiation of insulin action has a delay of less than 30 minutes.
"Our approach outperforms standard approaches because all our model parameters are estimated in real time. Our model's configuration of recursive estimator and optimal controller will constitute an effective artificial pancreas," said Wang.
The finding was published in the Journal of Diabetes Science and Technology.
