Safety and Efficacy of Artificial Pancreas With and Without a Meal Detection Module on Glycemic Control in Adolescents With Type 1 Diabetes After a Missed Bolus

NCT ID: NCT02909829

Last Updated: 2020-05-27

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 12 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2017-10-31
• Study Completion Date: 2019-10-11

Brief Summary

Despite current treatments for type 1 diabetes, maintaining blood glucose levels within a good range is a difficult task. A primary source for poor glucose control in adolescents is skipping insulin boluses at mealtimes. Advances in glucose sensors have motivated the research towards closed-loop delivery systems to automatically regulate glucose levels. Closed-loop delivery (artificial pancreas) is composed of an insulin pump, a continuous glucose sensor and a dosing algorithm that calculates the insulin dose to infuse based on sensor readings. The performance of a closed-loop delivery after a missed bolus may be improved if the computer program that calculates the insulin is enhanced with a meal detection module. The meal detection module will automatically detect the meal (which had no bolus delivered), and signal the delivery of more insulin.

The aim of this study is to assess the safety and efficacy of a closed-loop delivery with and without meal detection module compared to conventional pump therapy in regulating post-prandial glycemic levels after omission of a meal bolus.

The primary hypothesis is that closed-loop delivery with no meal detection module will reduce the mean increase in postprandial glucose levels after a missed bolus compared to conventional pump therapy.

Detailed Description

Despite current treatments for type 1 diabetes, maintaining blood glucose levels within a good range is a difficult task. A primary source for poor glucose control in adolescents is skipping insulin boluses at mealtimes. Advances in glucose sensors have motivated the research towards closed-loop delivery systems to automatically regulate glucose levels. Closed-loop delivery (artificial pancreas) is composed of an insulin pump, a continuous glucose sensor and a dosing algorithm that calculates the insulin dose to infuse based on sensor readings. The performance of a closed-loop delivery after a missed bolus may be improved if the computer program that calculates the insulin is enhanced with a meal detection module. The meal detection module will automatically detect the meal (which had no bolus delivered), and signal the delivery of more insulin.

The aim of this study is to conduct a randomized, three-way, cross-over trial to compare the efficacy of closed-loop delivery, closed-loop delivery with a meal detection module, and conventional pump therapy. The study aims to compare these three interventions for 9 hours in adolescents with poorly controlled type 1 diabetes.

Each 9 hours will include two meals of different carbohydrate content, of which one will not have a carbohydrate-matched prandial bolus. This study will allow for the assessment of the safety and efficacy of closed-loop delivery with and without a meal detection module compared to conventional pump therapy in regulating post-prandial glycaemia.

The aim of this study is to assess the safety and efficacy of a closed-loop delivery with and without meal detection module compared to conventional pump therapy in regulating post-prandial glycemic levels after omission of a meal bolus.

The primary hypothesis is that closed-loop delivery with no meal detection module will reduce the mean increase in postprandial glucose levels after a missed bolus compared to conventional pump therapy.

The secondary hypotheses are:

1. Closed-loop delivery with meal detection module will reduce the mean increase in postprandial glucose levels after a missed bolus compared to conventional pump therapy.

2. Closed-loop delivery with meal detection module will reduce the mean increase in postprandial glucose levels after a missed bolus compared to closed-loop delivery with no meal detection module.

Conditions

Diabetes Mellitus, Type 1

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: CROSSOVER
• Primary Study Purpose: TREATMENT
• Blinding Strategy: NONE

Study Groups

Closed Loop Delivery

Insulin will be delivered by subcutaneous insulin infusion pump. Infusion rates will be changed manually every 10 minutes based on the computer generated recommendation infusion rates, calculated from the glucose levels measured by a real time sensor. The computer generated recommendations are based on a predictive algorithm. Participants will eat breakfast and bolus, then eat lunch and not bolus.

Group Type: EXPERIMENTAL

Closed Loop Delivery

Intervention Type: DEVICE

Insulin will be delivered by subcutaneous insulin infusion pump. Infusion rates will be changed manually every 10 minutes based on the computer generated recommendation infusion rates, calculated from the glucose levels measured by a real time sensor. The computer generated recommendations are based on a predictive algorithm.

Closed Loop Delivery with Meal Detection Module

Insulin will be delivered by subcutaneous insulin infusion pump. Infusion rates will be changed manually every 10 minutes based on the computer generated recommendation infusion rates, calculated from the glucose levels measured by a real time sensor. The computer generated recommendations are based on a predictive algorithm with an overlying meal detection module which detects missed meals and will increase insulin infusion rates based on a predictive meal detection algorithm. Participants will eat breakfast and bolus, then eat lunch and not bolus.

Group Type: EXPERIMENTAL

Closed Loop Delivery with Meal Detection Module

Intervention Type: DEVICE

Closed Loop Delivery with Meal Detection Module Insulin will be delivered by subcutaneous insulin infusion pump. Infusion rates will be changed manually every 10 minutes based on the computer generated recommendation infusion rates, calculated from the glucose levels measured by a real time sensor. The computer generated recommendations are based on a predictive algorithm with an overlying meal detection module which detects missed meals and will increase insulin infusion rates based on a predictive meal detection algorithm

Conventional Pump Therapy

Insulin will be delivered by subcutaneous insulin infusion pump with participants usual infusion rate. Participants will eat breakfast and bolus as per usual, then eat lunch and not bolus.

Group Type: ACTIVE_COMPARATOR

Conventional Pump Therapy

Intervention Type: DEVICE

Insulin will be delivered by subcutaneous insulin infusion pump with participants usual infusion rate

Interventions

Closed Loop Delivery

Insulin will be delivered by subcutaneous insulin infusion pump. Infusion rates will be changed manually every 10 minutes based on the computer generated recommendation infusion rates, calculated from the glucose levels measured by a real time sensor. The computer generated recommendations are based on a predictive algorithm.

Intervention Type: DEVICE

Closed Loop Delivery with Meal Detection Module

Closed Loop Delivery with Meal Detection Module Insulin will be delivered by subcutaneous insulin infusion pump. Infusion rates will be changed manually every 10 minutes based on the computer generated recommendation infusion rates, calculated from the glucose levels measured by a real time sensor. The computer generated recommendations are based on a predictive algorithm with an overlying meal detection module which detects missed meals and will increase insulin infusion rates based on a predictive meal detection algorithm

Intervention Type: DEVICE

Conventional Pump Therapy

Insulin will be delivered by subcutaneous insulin infusion pump with participants usual infusion rate

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

1. Clinical diagnosis of type 1 diabetes for at least 12 months. (The diagnosis of type 1 diabetes is based on the investigator's judgment; C peptide level and antibody determinations are not needed.)

2. The participant will have been on insulin pump therapy for at least 3 months.

3. HbA1c 7.5% to 12%.

4. Self-reported or documented history of missed-bolus for meals during the previous 6 months.

Exclusion Criteria

1. Clinically significant nephropathy, neuropathy or retinopathy as judged by the investigator.

2. Severe hypoglycemic episode within one month of screening.

3. Pregnancy.

4. Current use of oral glucocorticoid medication (except low stable dose). Stable doses of inhaled steroids are acceptable.

5. Known or suspected allergy to the trial products, including the meal content.

6. Other serious medical illness likely to interfere with study participation or with the ability to complete the trial by the judgment of the investigator.

7. Failure to comply with team's recommendations (e.g. not willing to eat meals/snacks, not willing to change pump parameters, etc.).

• Minimum Eligible Age: 12 Years
• Maximum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

McGill University

OTHER

Sponsor Role: lead

Responsible Party

Ahmad Haidar

Assistant Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

McGill University Health Centre

Montreal, Quebec, Canada

Countries

Canada

Other Identifiers

Missed Bolus 9h

Identifier Type: -

Identifier Source: org_study_id