Real-time Adaptation to Changes in Insulin Sensitivity

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.

Conditions

• Type 1 Diabetes Mellitus

Interventions

DEVICE

The Fading Memory Proportional Derivative/Adaptive Proportional Derivative Algorithm

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.

DEVICE

The Adaptive Proportional Derivative Algorithm

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.

Sponsors & Collaborators

• Juvenile Diabetes Research Foundation

  collaborator OTHER

• Legacy Health System

  lead OTHER

Principal Investigators

• W K Ward, MD · Legacy Health Research

Study Design

Allocation

RANDOMIZED

Purpose

TREATMENT

Masking

SINGLE

Model

CROSSOVER

Eligibility

Min Age

21 Years

Max Age

65 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2010-11-30

Primary Completion

2011-04-30

Completion

2011-04-30

Countries

• United States

Study Locations