Trial Outcomes & Findings for Development of a Behavioral Observer for Type 1 Diabetes Mellitus (NCT NCT01434030)

Results Overview

The categories below indicate types of information that could be received from a PGASystem and the percentage of participants who stated that they would like to receive this type of information from a PGASystem.

Recruitment status

COMPLETED

Study phase

NA

Target enrollment

57 participants

Primary outcome timeframe

2 hour focus group

Results posted on

2014-09-04

Participant Flow

Participant milestones

Participant milestones
Measure	Behavioral Observer Focus group methodology was chosen to obtain qualitative and quantitative data on participants' desire to use glucose advisory systems to manage their diabetes, their concerns about and desired features and functions of these systems, and their perceived confidence with behavioral event recording. At the outset of each interview, the personalized glucose advisory system (PGASystem) was described to participants as a system composed of a continuous glucose monitor (CGM) device and insulin pump, into which they would input daily information about their insulin, food, and physical activity. The system would then use their data to create personalized algorithms and advice about various aspects of their diabetes management, such as suggestions regarding bolus and basal rate dosing. The interview consisted of open-ended, multiple choice, and dichotomous questions.
Overall Study STARTED	57
Overall Study COMPLETED	56
Overall Study NOT COMPLETED	1

Reasons for withdrawal

Withdrawal data not reported

Baseline Characteristics

Development of a Behavioral Observer for Type 1 Diabetes Mellitus

Baseline characteristics by cohort

Baseline characteristics by cohort
Measure	Behavioral Observer n=56 Participants Behavioral: This is a field study that will investigate behavioral events (e.g. meals, exercise) in T1DM and daily glucose patterns using an insulin pump, continuous glucose monitoring (CGM) data, and frequent SMBG tagged with behavioral markers (recent food and activity). From these data, a learning algorithm - behavioral observer - will be able to track over time key recurrent elements, such as wake-up time, meals, exercise, and daily patterns of risks for hypo- or hyperglycemia. In future controllers, behavioral observation such as this will be used to forecast upcoming routine events, enabling open-loop and closed-loop control algorithms to deal with the probabilistic patterns of patients' self-treatment behavior.
Age, Continuous	41 years STANDARD_DEVIATION 12.2 • n=5 Participants
Sex: Female, Male Female	33 Participants n=5 Participants
Sex: Female, Male Male	23 Participants n=5 Participants
HbA1c	7.7 percent glycated hemoglobin STANDARD_DEVIATION 1.2 • n=5 Participants
Duration of Diabetes	24.1 years STANDARD_DEVIATION 11.0 • n=5 Participants

PRIMARY outcome

Timeframe: 2 hour focus group

The categories below indicate types of information that could be received from a PGASystem and the percentage of participants who stated that they would like to receive this type of information from a PGASystem.

Outcome measures

Outcome measures
Measure	Behavioral Observer n=56 Participants Focus group methodology was chosen to obtain qualitative and quantitative data on participants' desire to use glucose advisory systems to manage their diabetes, their concerns about and desired features and functions of these systems, and their perceived confidence with behavioral event recording. At the outset of each interview, the personalized glucose advisory system (PGASystem) was described to participants as a system composed of a continuous glucose monitor (CGM) device and insulin pump, into which they would input daily information about their insulin, food, and physical activity. The system would then use their data to create personalized algorithms and advice about various aspects of their diabetes management, such as suggestions regarding bolus and basal rate dosing. The interview consisted of open-ended, multiple choice, and dichotomous questions.
Desire to Receive Advice From Personal Glucose Advisory System (PGASystem) Correction Boluses	100 percentage of participants
Desire to Receive Advice From Personal Glucose Advisory System (PGASystem) Basal Rates	92.9 percentage of participants
Desire to Receive Advice From Personal Glucose Advisory System (PGASystem) Meal Boluses/Inuslin to Carb Ratios	94.6 percentage of participants
Desire to Receive Advice From Personal Glucose Advisory System (PGASystem) Hypoglycemia Risk	85.7 percentage of participants

SECONDARY outcome

Timeframe: 2 hour focus group

The categories below indicate types of information that could be received from a PGASystem and the percentage of participants who stated that they would follow this type of advice from a PGASystem.

Outcome measures

Outcome measures
Measure	Behavioral Observer n=56 Participants Focus group methodology was chosen to obtain qualitative and quantitative data on participants' desire to use glucose advisory systems to manage their diabetes, their concerns about and desired features and functions of these systems, and their perceived confidence with behavioral event recording. At the outset of each interview, the personalized glucose advisory system (PGASystem) was described to participants as a system composed of a continuous glucose monitor (CGM) device and insulin pump, into which they would input daily information about their insulin, food, and physical activity. The system would then use their data to create personalized algorithms and advice about various aspects of their diabetes management, such as suggestions regarding bolus and basal rate dosing. The interview consisted of open-ended, multiple choice, and dichotomous questions.
Willingness to Follow PGASystem Advice Basal Rates	44.2 percentage of participants
Willingness to Follow PGASystem Advice Correction Boluses	53.6 percentage of participants
Willingness to Follow PGASystem Advice Meal Boluses	60.4 percentage of participants

Adverse Events

Behavioral Observer

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

Boris P Kovatchev, Ph.D.

University of Virginia

Phone: 434-924-5592

Email: [email protected]

Results disclosure agreements

Principal investigator is a sponsor employee
Publication restrictions are in place