Trial Outcomes & Findings for Closed-loop Glucose Control for Automated Management of Type 1 Diabetes (NCT NCT00811317)

NCT ID: NCT00811317

Last Updated: 2017-10-25

Results Overview

• Recruitment status: COMPLETED
• Study phase: NA
• Target enrollment: 11 participants
• Primary outcome timeframe: 24 hours
• Results posted on: 2017-10-25

Participant Flow

Participant milestones

Measure	Closed-loop Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Overall Study STARTED	11
Overall Study COMPLETED	11
Overall Study NOT COMPLETED	0

Reasons for withdrawal

Withdrawal data not reported

Baseline Characteristics

Closed-loop Glucose Control for Automated Management of Type 1 Diabetes

Baseline characteristics by cohort

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Age, Continuous	40 years STANDARD_DEVIATION 16 • n=5 Participants
Sex: Female, Male Female	4 Participants n=5 Participants
Sex: Female, Male Male	7 Participants n=5 Participants
Region of Enrollment United States	11 participants n=5 Participants

PRIMARY outcome

Timeframe: 24 hours

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Average Blood Glucose Over the Closed-loop Control Period	164 mg/dl Standard Deviation 17

SECONDARY outcome

Timeframe: 24 hours

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Percentage of Time Spent Within 70-180 mg/dl	61 percentage of time Standard Deviation 15

SECONDARY outcome

Timeframe: After each of 3 meals

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Peak Hyperglycemia Following Each Meal Breakfast	226.7 mg/dl Standard Deviation 26.6
Peak Hyperglycemia Following Each Meal Lunch	256.7 mg/dl Standard Deviation 30.7
Peak Hyperglycemia Following Each Meal Dinner	276.5 mg/dl Standard Deviation 33.8

SECONDARY outcome

Timeframe: After each of 3 meals

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Percentage of Time Spent in Hyperglycemia (BG> 180 mg/dl) After Meals	38 percentage of time Standard Deviation 9

SECONDARY outcome

Timeframe: 24 hours

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Percentage of Peak Post-prandial Hyperglycemias < 180 mg/dl (ADA Target) Breakfast	6 percentage of blood glucose measurements
Percentage of Peak Post-prandial Hyperglycemias < 180 mg/dl (ADA Target) Lunch	0 percentage of blood glucose measurements
Percentage of Peak Post-prandial Hyperglycemias < 180 mg/dl (ADA Target) Dinner	0 percentage of blood glucose measurements

SECONDARY outcome

Timeframe: 24 hours

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Percentage of Time Spent With BG < 70 mg/dl	0.35 percentage of time Standard Deviation 0.33

SECONDARY outcome

Timeframe: 24 hours

This outcome captures the number of hypoglycemic events that occurred throughout the entire study

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Number of Hypoglycemic Events	2 Number of events

SECONDARY outcome

Timeframe: 24 hours

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Nadir Blood Glucose Level for Each Hypoglycemic Event Event 1 of 2	66 mg/dl
Nadir Blood Glucose Level for Each Hypoglycemic Event Event 2 of 2	68 mg/dl

SECONDARY outcome

Timeframe: 24 hours

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Percentage of Time Spent With BG > 180 mg/dl	38 percentage of time Standard Deviation 2.9

SECONDARY outcome

Timeframe: 24 hours

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Total Insulin Dose	0.67 u/kg Standard Deviation 0.34

SECONDARY outcome

Timeframe: 24 hours

Time to maximum peak glucagon concentration

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Glucagon T-max	23 minutes Standard Deviation 9

SECONDARY outcome

Timeframe: 24 hours

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Total Glucagon Dose	3.5 mcg/kg Standard Deviation 2.8

SECONDARY outcome

Timeframe: 24 hours

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Blood Glucagon Levels	1.7 microgram/kg Standard Deviation 0.36

SECONDARY outcome

Timeframe: 24 hours

Population: Navigator CGM data from the day prior to admission was not obtained

Outcome measures

Outcome data not reported

SECONDARY outcome

Timeframe: 24 hours

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Number of Carbohydrate Interventions	0 number of interventions

SECONDARY outcome

Timeframe: 24 hours

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Number of Participants Achieving a Stable Glucose Response to Insulin Dosing	11 participants

SECONDARY outcome

Timeframe: 24 hours

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Number of Participants Achieving a Stable Glucose Response to Insulin Dosing Around Idle Times Prior to Meals	11 participants

SECONDARY outcome

Timeframe: 24 hours

Measuring the mean absolute relative difference (MARD) between the blood glucose measurement and CGM glucose readings, on three different CGM devices: Dexcom, Guardian and Navigator

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Accuracy of the Continuous Glucose Monitor (CGM) Using Blood Glucose Measurement as the Standard Navigator CGM	9.94 percent absolute difference Standard Deviation 10.09
Accuracy of the Continuous Glucose Monitor (CGM) Using Blood Glucose Measurement as the Standard Dexcom CGM	22.55 percent absolute difference Standard Deviation 20.75
Accuracy of the Continuous Glucose Monitor (CGM) Using Blood Glucose Measurement as the Standard Guardian CGM	18.04 percent absolute difference Standard Deviation 15.46

SECONDARY outcome

Timeframe: 24 hours

Population: This outcome was not analyzed. There were no experiments in non-diabetic subjects that we were able to make a comparison with

Outcome measures

Outcome data not reported

SECONDARY outcome

Timeframe: 24 hours

Population: This outcome was not analyzed. There were no open loop experiments in diabetic subjects that we were able to make a comparison with

Outcome measures

Outcome data not reported

SECONDARY outcome

Timeframe: 24 hours

Mean absolute relative difference (MARD) of CGM and BG glucose readings in hypoglycemia (< 70 mg/dl) and hyperglycemia (>180 mg/dl) in three different CGM devices: Dexcom, Navigator and Guardian

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Sensitivity for Hypo- and Hyperglycemia of the CGM Devices Using the BG Measurement as the Standard Dexcom < 70	18.90 percent absolute difference Standard Deviation 11.85
Sensitivity for Hypo- and Hyperglycemia of the CGM Devices Using the BG Measurement as the Standard Navigator < 70	18.64 percent absolute difference Standard Deviation 16.96
Sensitivity for Hypo- and Hyperglycemia of the CGM Devices Using the BG Measurement as the Standard Guardian < 70	36.46 percent absolute difference Standard Deviation 23.60
Sensitivity for Hypo- and Hyperglycemia of the CGM Devices Using the BG Measurement as the Standard Dexcom > 180	20.28 percent absolute difference Standard Deviation 15.34
Sensitivity for Hypo- and Hyperglycemia of the CGM Devices Using the BG Measurement as the Standard Navigator > 180	9.41 percent absolute difference Standard Deviation 8.78
Sensitivity for Hypo- and Hyperglycemia of the CGM Devices Using the BG Measurement as the Standard Guardian > 180	20.71 percent absolute difference Standard Deviation 16.95

SECONDARY outcome

Timeframe: 24 hours

The algorithm in the Bionic Pancreas must have a pre-specified target glucose it is trying to achieve in order to make dosing decisions. Using data from this study, investigators planned to determine what an appropriate glucose target should be for future studies.

Outcome measures

Measure	Closed-loop n=11 Participants Type 1 diabetic subjects under closed-loop blood glucose control Closed-loop: Computer algorithm developed by Firas El-Khatib and Edward Damiano at Boston University that controls sub-cutaneous infusion of insulin and glucagon to regulate blood glucose to target
Set Point Using CGM Data as the Input to the Controller for Future Studies	100 mg/dl

SECONDARY outcome

Timeframe: 24 hours

Population: This outcome was not analyzed. There were no experiments in non-diabetic subjects that we were able to make a comparison with

Outcome measures

Outcome data not reported

Adverse Events

Closed-loop

Serious events: 0 serious events

Other events: 0 other events

Deaths: 0 deaths

Serious adverse events

Adverse event data not reported

Other adverse events

Adverse event data not reported

Additional Information

Steven Russell

Massachusetts General Hospital

Phone: 6177261848

Email: sjrussell@mgh.harvard.edu

Results disclosure agreements

• Principal investigator is a sponsor employee
• Publication restrictions are in place