Real-time Adaptation to Changes in Insulin Sensitivity
Condition: Type 1 Diabetes Mellitus
MeSH terms: Diabetes Mellitus; Diabetes Mellitus, Type 1; Insulin Resistance
Study type: Interventional
Phase: Phase 2

Summary: 
      The purpose of this research study is to test an automated blood glucose control system that
      includes a new component designed to adapt to stress. The importance of this component is
      that when Type 1 Diabetics are stressed (for example, from illness or infection), their body
      is resistant to the effects of insulin. The investigators will be adjusting their blood
      glucose using insulin and glucagon and making their body less sensitive to insulin with a
      steroid, hydrocortisone. Insulin is a hormone that lowers blood glucose. Glucagon raises
      blood glucose when it is low. Both are natural hormones made by people without diabetes.
      Hydrocortisone is a steroid that will increase their blood glucose temporarily and will be
      given every 4 hours. All subjects will participate in two 33 hour experiments. One experiment
      will use the adaptive version of the sensor-based glucose control system. The other study
      will use the original version of the control system, without the adaptive component, for the
      first 13 hours. Then, the adaptive component will be added to the glucose control system for
      the remaining 20 hours of the study. Our primary goal is to assess the effectiveness of the
      adaptive component to control glucose levels in the presence of steroid-induced insulin
      resistance in persons with Type 1 Diabetes Mellitus.
    


Intervention name(s): The Fading Memory Proportional Derivative/Adaptive Proportional Derivative Algorithm; The Adaptive Proportional Derivative Algorithm
Intervention type(s): Device; Device
Intervention description(s): The APD algorithm is based largely on a program that employs the Fading Memory Proportional Derivative (FMPD) insulin and glucagon infusion algorithm. The FMPD algorithm determines insulin and glucagon delivery rates based on proportional error, defined as the difference between the current glucose level and the target level, and the derivative error, defined as the rate of change of the glucose. The "fading memory" designation refers to weighting recent errors more heavily than remote errors.
The APD algorithm, like the FMPD algorithm, will determine insulin and glucagon infusion rates based on sensed glucose values and utilizes the derivative and proportional glucose error to determine delivery rates of insulin. However, the APD algorithm has a model predictive element which also leads to frequent measurement of tissue sensitivity to insulin.; The APD algorithm is based largely on a program that employs the Fading Memory Proportional Derivative (FMPD) insulin and glucagon infusion algorithm. The FMPD algorithm determines insulin and glucagon delivery rates based on proportional error, defined as the difference between the current glucose level and the target level, and the derivative error, defined as the rate of change of the glucose. The "fading memory" designation refers to weighting recent errors more heavily than remote errors.
The APD algorithm, like the FMPD algorithm, will determine insulin and glucagon infusion rates based on sensed glucose values and utilizes the derivative and proportional glucose error to determine delivery rates of insulin. However, the APD algorithm has a model predictive element which also leads to frequent measurement of tissue sensitivity to insulin.
Allocation: Randomized
Intervention model: Crossover Assignment
Masking: Single (Participant)
Primary purpose: Treatment
Keywords: glucose sensors; artificial pancreas; Diabetes Mellitus