Trial Outcomes & Findings for Two Way Crossover Closed Loop Study MPC vs FMPD (NCT NCT04771403)

Last Updated: 2023-05-17

Results Overview

Assess the percent of time that the Dexcom G6 reported sensor glucose values less than 70 mg/dl using Dexcom sensor across the duration of the 12 hour inpatient stay (either Day 3 or Day 1 MPC vs. Day 1 FMPD).

Recruitment status

COMPLETED

Study phase

Target enrollment

25 participants

Primary outcome timeframe

12 hour inpatient stay (either Day 3 or Day 1 MPC vs. Day 1 FMPD)

Results posted on

2023-05-17

Participant Flow

Participant milestones

Participant milestones
Measure	MPC to FMPD The randomization order for participants in this arm was Model Predictive Control (MPC) followed by Fading-Memory Proportional Derivative (FMPD). Each visit was about 76 hours and included an inpatient and outpatient portion. The first 8 participants using the MPC remained as inpatients in clinic during the day and went home with system turned off at night (7pm-7am).	FMPD to MPC The randomization order for participants in this arm was Fading-Memory Proportional Derivative (FMPD) followed by Model Predictive Control (MPC). Each visit was about 76 hours and included an inpatient and outpatient portion. The first 8 participants using the MPC remained as inpatients in clinic during the day and went home with system turned off at night (7pm-7am).
Dexcom Training Visit (1 Week) STARTED	13	12
Dexcom Training Visit (1 Week) COMPLETED	13	12
Dexcom Training Visit (1 Week) NOT COMPLETED	0	0
First Rest Period (1-12 Weeks) STARTED	13	12
First Rest Period (1-12 Weeks) COMPLETED	13	12
First Rest Period (1-12 Weeks) NOT COMPLETED	0	0
First Intervention (~76 Hours) STARTED	13	12
First Intervention (~76 Hours) COMPLETED	9	10
First Intervention (~76 Hours) NOT COMPLETED	4	2
Second Rest Period (1-10 Weeks) STARTED	13	12
Second Rest Period (1-10 Weeks) COMPLETED	12	12
Second Rest Period (1-10 Weeks) NOT COMPLETED	1	0
Second Intervention Visit (~76 Hours) STARTED	12	12
Second Intervention Visit (~76 Hours) COMPLETED	11	12
Second Intervention Visit (~76 Hours) NOT COMPLETED	1	0

Reasons for withdrawal

Reasons for withdrawal
Measure	MPC to FMPD The randomization order for participants in this arm was Model Predictive Control (MPC) followed by Fading-Memory Proportional Derivative (FMPD). Each visit was about 76 hours and included an inpatient and outpatient portion. The first 8 participants using the MPC remained as inpatients in clinic during the day and went home with system turned off at night (7pm-7am).	FMPD to MPC The randomization order for participants in this arm was Fading-Memory Proportional Derivative (FMPD) followed by Model Predictive Control (MPC). Each visit was about 76 hours and included an inpatient and outpatient portion. The first 8 participants using the MPC remained as inpatients in clinic during the day and went home with system turned off at night (7pm-7am).
First Intervention (~76 Hours) FMPD study stopped after 7 hours: Pod occlusion with hyperglycemia (data not analyzed)	0	1
First Intervention (~76 Hours) MPC study stopped after 8 hours due to algorithm safety concerns (data not analyzed)	1	0
First Intervention (~76 Hours) MPC Study stopped after 34 hrs for safety due to high ketones (data analyzed)	1	0
First Intervention (~76 Hours) MPC study stopped after 61 hrs due to cloud server issues (data analyzed)	1	0
First Intervention (~76 Hours) MPC study stopped after 32 hours due to algorithm safety concerns (data analyzed)	1	0
First Intervention (~76 Hours) FMPD study stopped after 6 hours due to algorithm safety concerns (data not analyzed)	0	1
Second Rest Period (1-10 Weeks) Subject withdrawn before completing FMPD study due to safety concerns due to keto diet	1	0
Second Intervention Visit (~76 Hours) FMPD study stopped after 25 hrs due to stopping rules for hypoglycemia (data analyzed)	1	0

Baseline Characteristics

Two Way Crossover Closed Loop Study MPC vs FMPD

Baseline characteristics by cohort

Baseline characteristics by cohort
Measure	MPC to FMPD n=13 Participants The randomization order for participants in this arm was Model Predictive Control (MPC) followed by Fading-Memory Proportional Derivative (FMPD). Each visit was about 72 hours and included a 12 hour inpatient and 60 hour outpatient portion.	FMPD to MPC n=12 Participants The randomization order for participants in this arm was Fading-Memory Proportional Derivative (FMPD) followed by Model Predictive Control (MPC). Each visit was about 72 hours and included a 12 hour inpatient and 60 hour outpatient portion.	Total n=25 Participants Total of all reporting groups
Age, Categorical <=18 years	0 Participants n=5 Participants	0 Participants n=7 Participants	0 Participants n=5 Participants
Age, Categorical Between 18 and 65 years	13 Participants n=5 Participants	12 Participants n=7 Participants	25 Participants n=5 Participants
Age, Categorical >=65 years	0 Participants n=5 Participants	0 Participants n=7 Participants	0 Participants n=5 Participants
Age, Continuous	35.2 years STANDARD_DEVIATION 8.9 • n=5 Participants	33.4 years STANDARD_DEVIATION 8.9 • n=7 Participants	34.0 years STANDARD_DEVIATION 8.8 • n=5 Participants
Sex: Female, Male Female	9 Participants n=5 Participants	7 Participants n=7 Participants	16 Participants n=5 Participants
Sex: Female, Male Male	4 Participants n=5 Participants	5 Participants n=7 Participants	9 Participants n=5 Participants
Ethnicity (NIH/OMB) Hispanic or Latino	0 Participants n=5 Participants	0 Participants n=7 Participants	0 Participants n=5 Participants
Ethnicity (NIH/OMB) Not Hispanic or Latino	13 Participants n=5 Participants	12 Participants n=7 Participants	25 Participants n=5 Participants
Ethnicity (NIH/OMB) Unknown or Not Reported	0 Participants n=5 Participants	0 Participants n=7 Participants	0 Participants n=5 Participants
Race (NIH/OMB) American Indian or Alaska Native	0 Participants n=5 Participants	1 Participants n=7 Participants	1 Participants n=5 Participants
Race (NIH/OMB) Asian	0 Participants n=5 Participants	0 Participants n=7 Participants	0 Participants n=5 Participants
Race (NIH/OMB) Native Hawaiian or Other Pacific Islander	0 Participants n=5 Participants	0 Participants n=7 Participants	0 Participants n=5 Participants
Race (NIH/OMB) Black or African American	0 Participants n=5 Participants	0 Participants n=7 Participants	0 Participants n=5 Participants
Race (NIH/OMB) White	13 Participants n=5 Participants	9 Participants n=7 Participants	22 Participants n=5 Participants
Race (NIH/OMB) More than one race	0 Participants n=5 Participants	2 Participants n=7 Participants	2 Participants n=5 Participants
Race (NIH/OMB) Unknown or Not Reported	0 Participants n=5 Participants	0 Participants n=7 Participants	0 Participants n=5 Participants
Region of Enrollment United States	13 participants n=5 Participants	12 participants n=7 Participants	25 participants n=5 Participants

PRIMARY outcome

Timeframe: 12 hour inpatient stay (either Day 3 or Day 1 MPC vs. Day 1 FMPD)

Population: Out of 25 participants enrolled, the MPC study cancelled after 8 hours was not analyzed, the other three MPC studies that were cancelled after 30+ hours were analyzed. Two FMPD studies were cancelled the first day, 6 or 7 hours in and one FMPD study never happened as participant was withdrawn, so three FMPD studies were not analyzed. The other FMPD study that was cancelled after 28 hours was analyzed.

Outcome measures

Outcome measures
Measure	FMPD AP System n=22 Participants Participants will use the FMPD AP system for automated insulin delivery for a 76 hour study visit. FMPD AP algorithm: The Fading Memory Proportional Derivative (FMPD) insulin infusion algorithm determines insulin delivery rates based on proportional error, defined as the difference between the current CGM level and the target CGM level, and the derivative error, defined as the rate of change of the CGM. The FMPD algorithm utilizes derivative and proportional glucose errors to determine delivery rates of insulin.	MPC AP System n=24 Participants Participants will use the MPC AP system for automated insulin delivery for a 76 hour study visit. MPC AP system: The Model Predictive Control (MPC) insulin infusion algorithm contains a model within the controller that takes as an input the aerobic metabolic expenditure in addition to the CGM and meal inputs. The algorithm uses heart rate and accelerometer data collected on the patient's body to calculate metabolic expenditure. The metabolic expenditure then acts on the model for the insulin dynamics, whereby more energy expenditure and longer duration exercise can lead to a more substantial effect of insulin on the CGM.
Percent of Time With Sensed Glucose <70 mg/dl	2.5 percentage of time Standard Deviation 7.0	1.3 percentage of time Standard Deviation 2.9

SECONDARY outcome

Timeframe: During each 76 hour intervention study (2 total)

Assess the percent of time that the Dexcom G6 reported sensor glucose values between 70-180 mg/dl using Dexcom sensor across both arms.

Outcome measures

Outcome measures
Measure	FMPD AP System n=22 Participants Participants will use the FMPD AP system for automated insulin delivery for a 76 hour study visit. FMPD AP algorithm: The Fading Memory Proportional Derivative (FMPD) insulin infusion algorithm determines insulin delivery rates based on proportional error, defined as the difference between the current CGM level and the target CGM level, and the derivative error, defined as the rate of change of the CGM. The FMPD algorithm utilizes derivative and proportional glucose errors to determine delivery rates of insulin.	MPC AP System n=24 Participants Participants will use the MPC AP system for automated insulin delivery for a 76 hour study visit. MPC AP system: The Model Predictive Control (MPC) insulin infusion algorithm contains a model within the controller that takes as an input the aerobic metabolic expenditure in addition to the CGM and meal inputs. The algorithm uses heart rate and accelerometer data collected on the patient's body to calculate metabolic expenditure. The metabolic expenditure then acts on the model for the insulin dynamics, whereby more energy expenditure and longer duration exercise can lead to a more substantial effect of insulin on the CGM.
Percent of Time With Sensed Glucose Between 70-180 mg/dl	75.5 percentage of time Standard Deviation 10.7	71.2 percentage of time Standard Deviation 16.1

SECONDARY outcome

Timeframe: 12 hour inpatient stay (either Day 3 or Day 1 MPC vs. Day 1 FMPD)

Assess the percent of time that the Dexcom G6 reported sensor glucose values between 70-180 mg/dl using Dexcom sensor across the duration of the 12 hour inpatient stay (either Day 3 or Day 1 MPC vs. Day 1 FMPD).

Outcome measures

Outcome measures
Measure	FMPD AP System n=22 Participants Participants will use the FMPD AP system for automated insulin delivery for a 76 hour study visit. FMPD AP algorithm: The Fading Memory Proportional Derivative (FMPD) insulin infusion algorithm determines insulin delivery rates based on proportional error, defined as the difference between the current CGM level and the target CGM level, and the derivative error, defined as the rate of change of the CGM. The FMPD algorithm utilizes derivative and proportional glucose errors to determine delivery rates of insulin.	MPC AP System n=24 Participants Participants will use the MPC AP system for automated insulin delivery for a 76 hour study visit. MPC AP system: The Model Predictive Control (MPC) insulin infusion algorithm contains a model within the controller that takes as an input the aerobic metabolic expenditure in addition to the CGM and meal inputs. The algorithm uses heart rate and accelerometer data collected on the patient's body to calculate metabolic expenditure. The metabolic expenditure then acts on the model for the insulin dynamics, whereby more energy expenditure and longer duration exercise can lead to a more substantial effect of insulin on the CGM.
Percent of Time With Sensed Glucose Between 70 - 180 mg/dl	59.4 percentage of time Standard Deviation 23.1	63.2 percentage of time Standard Deviation 23.9

SECONDARY outcome

Timeframe: start of the in-clinic exercise session until the start of the next meal, approximately 1 hour

Assess the percent of time that the Dexcom G6 reported sensor glucose values between 70-180 mg/dl using Dexcom sensor across both arms from the start of the in-clinic exercise session until the start of the next meal.

Outcome measures

Outcome measures
Measure	FMPD AP System n=22 Participants Participants will use the FMPD AP system for automated insulin delivery for a 76 hour study visit. FMPD AP algorithm: The Fading Memory Proportional Derivative (FMPD) insulin infusion algorithm determines insulin delivery rates based on proportional error, defined as the difference between the current CGM level and the target CGM level, and the derivative error, defined as the rate of change of the CGM. The FMPD algorithm utilizes derivative and proportional glucose errors to determine delivery rates of insulin.	MPC AP System n=24 Participants Participants will use the MPC AP system for automated insulin delivery for a 76 hour study visit. MPC AP system: The Model Predictive Control (MPC) insulin infusion algorithm contains a model within the controller that takes as an input the aerobic metabolic expenditure in addition to the CGM and meal inputs. The algorithm uses heart rate and accelerometer data collected on the patient's body to calculate metabolic expenditure. The metabolic expenditure then acts on the model for the insulin dynamics, whereby more energy expenditure and longer duration exercise can lead to a more substantial effect of insulin on the CGM.
Percent of Time With Sensed Glucose Between 70 - 180 mg/dl After Exercise	81 percentage of time Standard Deviation 22	87 percentage of time Standard Deviation 17

SECONDARY outcome

Timeframe: start of the in-clinic exercise session until the start of the next meal, approximately 1 hour

Assess the percent of time that the Dexcom G6 reported sensor glucose values less than 70 mg/dl using Dexcom sensor across both arms from the start of the in-clinic exercise session until the start of the next meal.

Outcome measures

Outcome measures
Measure	FMPD AP System n=22 Participants Participants will use the FMPD AP system for automated insulin delivery for a 76 hour study visit. FMPD AP algorithm: The Fading Memory Proportional Derivative (FMPD) insulin infusion algorithm determines insulin delivery rates based on proportional error, defined as the difference between the current CGM level and the target CGM level, and the derivative error, defined as the rate of change of the CGM. The FMPD algorithm utilizes derivative and proportional glucose errors to determine delivery rates of insulin.	MPC AP System n=24 Participants Participants will use the MPC AP system for automated insulin delivery for a 76 hour study visit. MPC AP system: The Model Predictive Control (MPC) insulin infusion algorithm contains a model within the controller that takes as an input the aerobic metabolic expenditure in addition to the CGM and meal inputs. The algorithm uses heart rate and accelerometer data collected on the patient's body to calculate metabolic expenditure. The metabolic expenditure then acts on the model for the insulin dynamics, whereby more energy expenditure and longer duration exercise can lead to a more substantial effect of insulin on the CGM.
Percent of Time With Sensed Glucose <70 mg/dl After Exercise	4.9 percentage of time Standard Deviation 14.4	1.4 percentage of time Standard Deviation 4.2

SECONDARY outcome

Timeframe: During each 76 hour intervention study (2 total)

Assess the mean number of carbohydrate treatments (defined as 15 or 20 grams of carbohydrate) across both arms.

Outcome measures

Outcome measures
Measure	FMPD AP System n=22 Participants Participants will use the FMPD AP system for automated insulin delivery for a 76 hour study visit. FMPD AP algorithm: The Fading Memory Proportional Derivative (FMPD) insulin infusion algorithm determines insulin delivery rates based on proportional error, defined as the difference between the current CGM level and the target CGM level, and the derivative error, defined as the rate of change of the CGM. The FMPD algorithm utilizes derivative and proportional glucose errors to determine delivery rates of insulin.	MPC AP System n=24 Participants Participants will use the MPC AP system for automated insulin delivery for a 76 hour study visit. MPC AP system: The Model Predictive Control (MPC) insulin infusion algorithm contains a model within the controller that takes as an input the aerobic metabolic expenditure in addition to the CGM and meal inputs. The algorithm uses heart rate and accelerometer data collected on the patient's body to calculate metabolic expenditure. The metabolic expenditure then acts on the model for the insulin dynamics, whereby more energy expenditure and longer duration exercise can lead to a more substantial effect of insulin on the CGM.
Number of Carbohydrate Treatments	1.03 carbohydrate treatments/day Standard Deviation 1.34	0.65 carbohydrate treatments/day Standard Deviation 0.84

SECONDARY outcome

Timeframe: During each 76 hour intervention study (2 total)

Assess the mean sensed glucose from the Dexcom G6 reported sensor glucose values across both arms. The Dexcom G6 CGM updates every 5 minutes with a new CGM value for 10 days. The Dexcom G6 reads values between 40-400 mg/dL with an urgent low alert at 55 mg/dl, a low and high alert when CGM goes above or below the alert thresholds set by the user. Physiologically relevant thresholds for the Dexcom G6 CGM sensor glucose values are less than 55 mg/dl, less than 70 mg/dl, above 180 mg/dl and above 250 mg/dl. The Dexcom G6 target range is 70-180 mg/dl.

Outcome measures

Outcome measures
Measure	FMPD AP System n=22 Participants Participants will use the FMPD AP system for automated insulin delivery for a 76 hour study visit. FMPD AP algorithm: The Fading Memory Proportional Derivative (FMPD) insulin infusion algorithm determines insulin delivery rates based on proportional error, defined as the difference between the current CGM level and the target CGM level, and the derivative error, defined as the rate of change of the CGM. The FMPD algorithm utilizes derivative and proportional glucose errors to determine delivery rates of insulin.	MPC AP System n=24 Participants Participants will use the MPC AP system for automated insulin delivery for a 76 hour study visit. MPC AP system: The Model Predictive Control (MPC) insulin infusion algorithm contains a model within the controller that takes as an input the aerobic metabolic expenditure in addition to the CGM and meal inputs. The algorithm uses heart rate and accelerometer data collected on the patient's body to calculate metabolic expenditure. The metabolic expenditure then acts on the model for the insulin dynamics, whereby more energy expenditure and longer duration exercise can lead to a more substantial effect of insulin on the CGM.
Mean Sensed Glucose	8.5 mmol/L Standard Deviation 0.9	8.8 mmol/L Standard Deviation 1.3

SECONDARY outcome

Timeframe: During each 76 hour intervention study (2 total)

Assess the coefficient of variation of glucose from the Dexcom G6 reported sensor glucose values across both arms. The Dexcom G6 CGM updates every 5 minutes with a new CGM value for 10 days. The Dexcom G6 reads values between 40-400 mg/dL with an urgent low alert at 55 mg/dl, a low and high alert when CGM goes above or below the alert thresholds set by the user. Physiologically relevant thresholds for the Dexcom G6 CGM sensor glucose values are less than 55 mg/dl, less than 70 mg/dl, above 180 mg/dl and above 250 mg/dl. The Dexcom G6 target range is 70-180 mg/dl.The target coefficient of variation is 33% or lower.

Outcome measures

Outcome measures
Measure	FMPD AP System n=22 Participants Participants will use the FMPD AP system for automated insulin delivery for a 76 hour study visit. FMPD AP algorithm: The Fading Memory Proportional Derivative (FMPD) insulin infusion algorithm determines insulin delivery rates based on proportional error, defined as the difference between the current CGM level and the target CGM level, and the derivative error, defined as the rate of change of the CGM. The FMPD algorithm utilizes derivative and proportional glucose errors to determine delivery rates of insulin.	MPC AP System n=24 Participants Participants will use the MPC AP system for automated insulin delivery for a 76 hour study visit. MPC AP system: The Model Predictive Control (MPC) insulin infusion algorithm contains a model within the controller that takes as an input the aerobic metabolic expenditure in addition to the CGM and meal inputs. The algorithm uses heart rate and accelerometer data collected on the patient's body to calculate metabolic expenditure. The metabolic expenditure then acts on the model for the insulin dynamics, whereby more energy expenditure and longer duration exercise can lead to a more substantial effect of insulin on the CGM.
Coefficient of Variation of Glucose	28.4 percentage Standard Deviation 5.9	29.6 percentage Standard Deviation 6.9

SECONDARY outcome

Timeframe: During each 76 hour intervention study (2 total)

Assess the percent of time that the Dexcom G6 reported sensor glucose values less than 54 mg/dl using Dexcom sensor across both arms

Outcome measures

Outcome measures
Measure	FMPD AP System n=22 Participants Participants will use the FMPD AP system for automated insulin delivery for a 76 hour study visit. FMPD AP algorithm: The Fading Memory Proportional Derivative (FMPD) insulin infusion algorithm determines insulin delivery rates based on proportional error, defined as the difference between the current CGM level and the target CGM level, and the derivative error, defined as the rate of change of the CGM. The FMPD algorithm utilizes derivative and proportional glucose errors to determine delivery rates of insulin.	MPC AP System n=24 Participants Participants will use the MPC AP system for automated insulin delivery for a 76 hour study visit. MPC AP system: The Model Predictive Control (MPC) insulin infusion algorithm contains a model within the controller that takes as an input the aerobic metabolic expenditure in addition to the CGM and meal inputs. The algorithm uses heart rate and accelerometer data collected on the patient's body to calculate metabolic expenditure. The metabolic expenditure then acts on the model for the insulin dynamics, whereby more energy expenditure and longer duration exercise can lead to a more substantial effect of insulin on the CGM.
Percent of Time With Sensed Glucose <54 mg/dl	0.13 percentage of time Standard Deviation 0.33	0.05 percentage of time Standard Deviation 0.15

SECONDARY outcome

Timeframe: During each 76 hour intervention study (2 total)

Assess the percent of time that the Dexcom G6 reported sensor glucose values greater than 180 mg/dl using Dexcom sensor across both arms

Outcome measures

Outcome measures
Measure	FMPD AP System n=22 Participants Participants will use the FMPD AP system for automated insulin delivery for a 76 hour study visit. FMPD AP algorithm: The Fading Memory Proportional Derivative (FMPD) insulin infusion algorithm determines insulin delivery rates based on proportional error, defined as the difference between the current CGM level and the target CGM level, and the derivative error, defined as the rate of change of the CGM. The FMPD algorithm utilizes derivative and proportional glucose errors to determine delivery rates of insulin.	MPC AP System n=24 Participants Participants will use the MPC AP system for automated insulin delivery for a 76 hour study visit. MPC AP system: The Model Predictive Control (MPC) insulin infusion algorithm contains a model within the controller that takes as an input the aerobic metabolic expenditure in addition to the CGM and meal inputs. The algorithm uses heart rate and accelerometer data collected on the patient's body to calculate metabolic expenditure. The metabolic expenditure then acts on the model for the insulin dynamics, whereby more energy expenditure and longer duration exercise can lead to a more substantial effect of insulin on the CGM.
Percent of Time With Sensed Glucose >180 mg/dl	23.2 percentage of time Standard Deviation 10.9	27.8 percentage of time Standard Deviation 16.0

SECONDARY outcome

Timeframe: During each 76 hour intervention study (2 total)

Assess the mean amount of insulin delivered per day by the Omnipod through the AP system study in units/kg across both arms.

Outcome measures

Outcome measures
Measure	FMPD AP System n=22 Participants Participants will use the FMPD AP system for automated insulin delivery for a 76 hour study visit. FMPD AP algorithm: The Fading Memory Proportional Derivative (FMPD) insulin infusion algorithm determines insulin delivery rates based on proportional error, defined as the difference between the current CGM level and the target CGM level, and the derivative error, defined as the rate of change of the CGM. The FMPD algorithm utilizes derivative and proportional glucose errors to determine delivery rates of insulin.	MPC AP System n=24 Participants Participants will use the MPC AP system for automated insulin delivery for a 76 hour study visit. MPC AP system: The Model Predictive Control (MPC) insulin infusion algorithm contains a model within the controller that takes as an input the aerobic metabolic expenditure in addition to the CGM and meal inputs. The algorithm uses heart rate and accelerometer data collected on the patient's body to calculate metabolic expenditure. The metabolic expenditure then acts on the model for the insulin dynamics, whereby more energy expenditure and longer duration exercise can lead to a more substantial effect of insulin on the CGM.
Mean Amount of Insulin Delivered Per Day (in Units/Day)	40.8 units/day Standard Deviation 16.0	44.6 units/day Standard Deviation 22.6

Adverse Events

MPC AP System

Serious events: 0 serious events

Other events: 1 other events

Deaths: 0 deaths

FMPD AP System

Serious events: 0 serious events

Other events: 0 other events

Deaths: 0 deaths

Dexcom G6 Training Arm

Serious events: 0 serious events

Other events: 1 other events

Deaths: 0 deaths

Serious adverse events

Adverse event data not reported

Other adverse events

Other adverse events
Measure	MPC AP System n=25 participants at risk Participants will use the MPC AP system for automated insulin delivery for a 76 hour study visit.	FMPD AP System n=24 participants at risk Participants will use the FMPD AP system for automated insulin delivery for a 76 hour study visit.	Dexcom G6 Training Arm n=25 participants at risk Participants will use the Dexcom G6 CGM with the MPC AP algorithm for acquiring sensor glucose values.
Nervous system disorders Headache	4.0% 1/25 • Number of events 1 • 12 months All participants that began/started the Dexcom training visit or an MPC or FMPD arm visit are included in the adverse events. The numbers from the participant flow indicate that 25 subjects began the Dexcom training visit, 25 subjects began an MPC visit and 24 subjects began an FMPD visit.	0.00% 0/24 • 12 months All participants that began/started the Dexcom training visit or an MPC or FMPD arm visit are included in the adverse events. The numbers from the participant flow indicate that 25 subjects began the Dexcom training visit, 25 subjects began an MPC visit and 24 subjects began an FMPD visit.	0.00% 0/25 • 12 months All participants that began/started the Dexcom training visit or an MPC or FMPD arm visit are included in the adverse events. The numbers from the participant flow indicate that 25 subjects began the Dexcom training visit, 25 subjects began an MPC visit and 24 subjects began an FMPD visit.
Musculoskeletal and connective tissue disorders Back Sprain	0.00% 0/25 • 12 months All participants that began/started the Dexcom training visit or an MPC or FMPD arm visit are included in the adverse events. The numbers from the participant flow indicate that 25 subjects began the Dexcom training visit, 25 subjects began an MPC visit and 24 subjects began an FMPD visit.	0.00% 0/24 • 12 months All participants that began/started the Dexcom training visit or an MPC or FMPD arm visit are included in the adverse events. The numbers from the participant flow indicate that 25 subjects began the Dexcom training visit, 25 subjects began an MPC visit and 24 subjects began an FMPD visit.	4.0% 1/25 • Number of events 1 • 12 months All participants that began/started the Dexcom training visit or an MPC or FMPD arm visit are included in the adverse events. The numbers from the participant flow indicate that 25 subjects began the Dexcom training visit, 25 subjects began an MPC visit and 24 subjects began an FMPD visit.
Blood and lymphatic system disorders High ketones	4.0% 1/25 • Number of events 1 • 12 months All participants that began/started the Dexcom training visit or an MPC or FMPD arm visit are included in the adverse events. The numbers from the participant flow indicate that 25 subjects began the Dexcom training visit, 25 subjects began an MPC visit and 24 subjects began an FMPD visit.	0.00% 0/24 • 12 months All participants that began/started the Dexcom training visit or an MPC or FMPD arm visit are included in the adverse events. The numbers from the participant flow indicate that 25 subjects began the Dexcom training visit, 25 subjects began an MPC visit and 24 subjects began an FMPD visit.	0.00% 0/25 • 12 months All participants that began/started the Dexcom training visit or an MPC or FMPD arm visit are included in the adverse events. The numbers from the participant flow indicate that 25 subjects began the Dexcom training visit, 25 subjects began an MPC visit and 24 subjects began an FMPD visit.

Additional Information

Jessica Castle

Oregon Health and Science University

Phone: 503-494-7072

Email: [email protected]

Results disclosure agreements

Principal investigator is a sponsor employee
Publication restrictions are in place