Trial Outcomes & Findings for DailyDose Smart Snack Study for T1D on MDI (NCT NCT05967260)
NCT ID: NCT05967260
Last Updated: 2025-05-31
Results Overview
An episode of overnight hypoglycemia is counted if sensor glucose is \<70 mg/dL for at least two measurements during an eight-hour period following announced bedtime. This is assessed by number of episodes divided by total number of nights.
Recruitment status
COMPLETED
Study phase
NA
Target enrollment
21 participants
Primary outcome timeframe
8 weeks (4-week control period vs. 4-week intervention period)
Results posted on
2025-05-31
Participant Flow
Participant milestones
| Measure |
Control to Intervention
The randomization order for participants in this arm was Dexcom G6 CGM (control) followed by DailyDose Smart Snack (intervention). Each arm was 4 weeks long.
|
Intervention to Control
The randomization order for participants in this arm was DailyDose Smart Snack (intervention) followed by Dexcom G6 CGM (control). Each arm was 4 weeks long.
|
|---|---|---|
|
First Rest Period (1-12 Weeks)
STARTED
|
10
|
11
|
|
First Rest Period (1-12 Weeks)
COMPLETED
|
10
|
10
|
|
First Rest Period (1-12 Weeks)
NOT COMPLETED
|
0
|
1
|
|
First Arm Start-up Visit (4 Weeks)
STARTED
|
10
|
10
|
|
First Arm Start-up Visit (4 Weeks)
COMPLETED
|
10
|
9
|
|
First Arm Start-up Visit (4 Weeks)
NOT COMPLETED
|
0
|
1
|
|
Second Rest Period (1-4 Weeks)
STARTED
|
10
|
10
|
|
Second Rest Period (1-4 Weeks)
COMPLETED
|
10
|
10
|
|
Second Rest Period (1-4 Weeks)
NOT COMPLETED
|
0
|
0
|
|
Second Arm Start-up Visit
STARTED
|
10
|
10
|
|
Second Arm Start-up Visit
COMPLETED
|
9
|
10
|
|
Second Arm Start-up Visit
NOT COMPLETED
|
1
|
0
|
|
Third Rest Period (1-2 Weeks)
STARTED
|
9
|
10
|
|
Third Rest Period (1-2 Weeks)
COMPLETED
|
9
|
10
|
|
Third Rest Period (1-2 Weeks)
NOT COMPLETED
|
0
|
0
|
|
Study Completion Visit
STARTED
|
9
|
10
|
|
Study Completion Visit
COMPLETED
|
9
|
10
|
|
Study Completion Visit
NOT COMPLETED
|
0
|
0
|
Reasons for withdrawal
| Measure |
Control to Intervention
The randomization order for participants in this arm was Dexcom G6 CGM (control) followed by DailyDose Smart Snack (intervention). Each arm was 4 weeks long.
|
Intervention to Control
The randomization order for participants in this arm was DailyDose Smart Snack (intervention) followed by Dexcom G6 CGM (control). Each arm was 4 weeks long.
|
|---|---|---|
|
First Arm Start-up Visit (4 Weeks)
Dexcom CGM failed while participant out of town without ability to receive a replacement
|
0
|
1
|
Baseline Characteristics
DailyDose Smart Snack Study for T1D on MDI
Baseline characteristics by cohort
| Measure |
Control to Intervention
n=10 Participants
The randomization order for participants in this arm was Dexcom G6 CGM (control) followed by DailyDose Smart Snack (intervention). Each arm was 4 weeks long.
|
Intervention to Control
n=11 Participants
The randomization order for participants in this arm was DailyDose Smart Snack (intervention) followed by Dexcom G6 CGM (control). Each arm was 4 weeks long.
|
Total
n=21 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
|
9 Participants
n=5 Participants
|
10 Participants
n=7 Participants
|
19 Participants
n=5 Participants
|
|
Age, Categorical
>=65 years
|
1 Participants
n=5 Participants
|
1 Participants
n=7 Participants
|
2 Participants
n=5 Participants
|
|
Age, Continuous
|
41.2 years
STANDARD_DEVIATION 14.6 • n=5 Participants
|
37 years
STANDARD_DEVIATION 15.1 • n=7 Participants
|
39 years
STANDARD_DEVIATION 14.7 • n=5 Participants
|
|
Sex: Female, Male
Female
|
3 Participants
n=5 Participants
|
7 Participants
n=7 Participants
|
10 Participants
n=5 Participants
|
|
Sex: Female, Male
Male
|
7 Participants
n=5 Participants
|
4 Participants
n=7 Participants
|
11 Participants
n=5 Participants
|
|
Race (NIH/OMB)
American Indian or Alaska Native
|
0 Participants
n=5 Participants
|
0 Participants
n=7 Participants
|
0 Participants
n=5 Participants
|
|
Race (NIH/OMB)
Asian
|
0 Participants
n=5 Participants
|
2 Participants
n=7 Participants
|
2 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
|
1 Participants
n=5 Participants
|
1 Participants
n=7 Participants
|
2 Participants
n=5 Participants
|
|
Race (NIH/OMB)
White
|
9 Participants
n=5 Participants
|
7 Participants
n=7 Participants
|
16 Participants
n=5 Participants
|
|
Race (NIH/OMB)
More than one race
|
0 Participants
n=5 Participants
|
1 Participants
n=7 Participants
|
1 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
|
10 participants
n=5 Participants
|
11 participants
n=7 Participants
|
21 participants
n=5 Participants
|
PRIMARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)An episode of overnight hypoglycemia is counted if sensor glucose is \<70 mg/dL for at least two measurements during an eight-hour period following announced bedtime. This is assessed by number of episodes divided by total number of nights.
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Probability of Overnight Hypoglycemia
|
23.6 percentage of nights
Standard Deviation 15.6
|
26.0 percentage of nights
Standard Deviation 14.1
|
SECONDARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)Number of hours until first CGM measurement \<70 mg/dL when CGM remains \< 70 mg/dL for at least 10 minutes.
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Time to the First Overnight Low-glucose Event (<70 mg/dL)
|
2.8 hours
Standard Deviation 1.4
|
3.3 hours
Standard Deviation 1.4
|
SECONDARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)Assess the mean percentage of time that the Dexcom G6 reported sensor glucose values are less than 54 mg/dL overnight (announced bedtime + 8 hours).
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Percentage of Time With Sensed Glucose Less Than 54 mg/dL (Overnight)
|
1.0 percentage of time
Standard Deviation 1.5
|
1.3 percentage of time
Standard Deviation 3.2
|
SECONDARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)Assess the mean percentage of time that the Dexcom G6 reported sensor glucose values are less than 54 mg/dL across the full 24-hour/day study duration.
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Percentage of Time With Sensed Glucose Less Than 54 mg/dL (24-hour/Day Study Duration)
|
0.7 percentage of time
Standard Deviation 0.7
|
0.7 percentage of time
Standard Deviation 1.0
|
SECONDARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)Assess the mean percentage of time that the Dexcom G6 reported sensor glucose values are less than 70 mg/dL overnight (announced bedtime + 8 hours).
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Percentage of Time With Sensed Glucose Less Than 70 mg/dL (Overnight)
|
4.2 percentage of time
Standard Deviation 3.8
|
4.7 percentage of time
Standard Deviation 5.5
|
SECONDARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)Assess the mean percentage of time that the Dexcom G6 reported sensor glucose values are less than 70 mg/dL across the 24-hour/day study duration.
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Percentage of Time With Sensed Glucose Less Than 70 mg/dL (24-hour/Day Study Duration)
|
3.2 percentage of time
Standard Deviation 1.8
|
3.1 percentage of time
Standard Deviation 2.3
|
SECONDARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)Assess the mean percentage of time that the Dexcom G6 reported sensor glucose values are between 70 and 180 mg/dL overnight (announced bedtime + 8 hours).
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Percentage of Time With Sensed Glucose Between 70-180 mg/dL (Overnight)
|
64.0 percentage of time
Standard Deviation 14.4
|
61.8 percentage of time
Standard Deviation 14.8
|
SECONDARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)Assess the mean percentage of time that the Dexcom G6 reported sensor glucose values are between 70 and 180 mg/dL across the full 24-hour/day study duration.
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Percentage of Time With Sensed Glucose Between 70-180 mg/dL (24-hour/Day Study Duration)
|
63.9 percentage of time
Standard Deviation 14.9
|
61.4 percentage of time
Standard Deviation 16.5
|
SECONDARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)Assess the mean percentage of time that the Dexcom G6 reported sensor glucose values are greater than 180 mg/dL overnight (announced bedtime + 8 hours).
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Percentage of Time With Sensed Glucose Greater Than 180 mg/dL (Overnight)
|
31.7 percentage of time
Standard Deviation 15.6
|
33.5 percentage of time
Standard Deviation 16.1
|
SECONDARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)Assess the mean percentage of time that the Dexcom G6 reported sensor glucose values are greater than 180 mg/dL across the full 24-hour/day study duration.
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Percentage of Time With Sensed Glucose Greater Than 180 mg/dL (24-hour/Day Study Duration)
|
32.8 percentage of time
Standard Deviation 15.3
|
35.5 percentage of time
Standard Deviation 16.6
|
SECONDARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)Assess the mean percentage of time that the Dexcom G6 reported sensor glucose values are greater than 250 mg/dL overnight (announced bedtime + 8 hours).
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Percentage of Time Sensed Glucose Greater Than 250 mg/dL (Overnight)
|
10.2 percentage of time
Standard Deviation 8.9
|
9.7 percentage of time
Standard Deviation 9.0
|
SECONDARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)Assess the mean percentage of time that the Dexcom G6 reported sensor glucose values are greater than 250 mg/dL across the full 24-hour/day study duration.
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Percentage of Time Sensed Glucose Greater Than 250 mg/dL (24-hour/Day Study Duration)
|
10.4 percentage of time
Standard Deviation 9.5
|
11.3 percentage of time
Standard Deviation 10.8
|
SECONDARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)Assess the mean reported sensor glucose values overnight (announced bedtime + 8 hours) using the Dexcom sensor.
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Mean Sensed Glucose (Overnight)
|
159.0 mg/dL
Standard Deviation 25.1
|
160.4 mg/dL
Standard Deviation 26.5
|
SECONDARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)Assess the mean reported sensor glucose values across the full 24-hour/day study duration using the Dexcom sensor.
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Mean Sensed Glucose (24-hour/Day Study Duration)
|
161.9 mg/dL
Standard Deviation 24.2
|
165.2 mg/dL
Standard Deviation 27.3
|
SECONDARY outcome
Timeframe: 4 weeks of control periodAssessment of accuracy of the overnight low glucose prediction algorithm by sensitivity. This is measured by the number of true positives that the algorithm predicts hypoglycemia overnight divided by all of the hypoglycemic events.
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Accuracy of Overnight Low Glucose Prediction by Sensitivity
|
71.6 percentage of true positive events
|
—
|
SECONDARY outcome
Timeframe: 4 weeks of control periodAssessment of accuracy of the overnight low glucose prediction algorithm by specificity. This is measured by calculating 1.0 minus the false positive rate for overnight hypoglycemia prediction.
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Accuracy of Overnight Low Glucose Prediction by Specificity
|
56.8 percentage of true negative events
|
—
|
SECONDARY outcome
Timeframe: 8 weeks (4-week control period vs. 4-week intervention period)Asses mean weight change from start to end of each arm.
Outcome measures
| Measure |
Intervention
n=20 Participants
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
DailyDose Smart Snack app: A decision support tool that predicts the likelihood of overnight low blood sugar based on current CGM and inputted exercise. App will recommend a snack at bedtime based on the minimum low glucose predicted and the time of the low glucose.
|
Control
n=20 Participants
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
Dexcom G6 CGM: A commercially available Continuous Glucose Monitoring system that utilizes a transmitter and sensor to measure sensor glucose levels that transmit to a smart phone app.
|
|---|---|---|
|
Change in Weight
|
-2.1 kg
Standard Deviation 3.0
|
-0.7 kg
Standard Deviation 1.3
|
Adverse Events
Active Comparator: Control
Serious events: 0 serious events
Other events: 1 other events
Deaths: 0 deaths
Experimental: Intervention
Serious events: 0 serious events
Other events: 1 other events
Deaths: 0 deaths
Serious adverse events
Adverse event data not reported
Other adverse events
| Measure |
Active Comparator: Control
n=20 participants at risk
Participants will wear Dexcom G6 CGM and will manage their glucose as usual. Participants will be asked to wear a smart watch overnight to collect sleep metrics, weigh themselves weekly in the morning before eating, and answer a one-item sleep quality scale survey weekly.
|
Experimental: Intervention
n=20 participants at risk
Participants will use the DailyDose Smart Snack smart phone application which contains an AI-based model that predicts the likelihood of overnight low glucose at bedtime every night and will recommend a personalized snack to help avoid nocturnal hypoglycemia. The nutritional content of the snack (carbohydrate, protein, fat, etc.) will be dependent on the predicted overnight minimum glucose and the predicted time of the minimum overnight glucose level. During this arm, participants will also be asked to wear a smart watch overnight, weigh themselves weekly, and answer a one-item sleep quality scale survey weekly.
|
|---|---|---|
|
Infections and infestations
Upper respiratory infection
|
0.00%
0/20 • Up to 8 weeks
All participants that began/started the first rest period after randomization are included in the adverse events. The numbers from the participant flow indicate that 21 subjects began the first rest period.
|
5.0%
1/20 • Number of events 1 • Up to 8 weeks
All participants that began/started the first rest period after randomization are included in the adverse events. The numbers from the participant flow indicate that 21 subjects began the first rest period.
|
|
Infections and infestations
Acute sinusitis
|
5.0%
1/20 • Number of events 1 • Up to 8 weeks
All participants that began/started the first rest period after randomization are included in the adverse events. The numbers from the participant flow indicate that 21 subjects began the first rest period.
|
0.00%
0/20 • Up to 8 weeks
All participants that began/started the first rest period after randomization are included in the adverse events. The numbers from the participant flow indicate that 21 subjects began the first rest period.
|
Additional Information
Clara Mosquera-Lopez
Oregon Health & Science University
Phone: 503--418-4129
Email: [email protected]
Results disclosure agreements
- Principal investigator is a sponsor employee
- Publication restrictions are in place