Back to resultsValidation of Machine Learning Based Personalized Nutrition Algorithm to Reduce Postprandial Glycemic Excursions Among North American Individuals With Newly Diagnosed Type 2 Diabetes
Primary Purpose
Type2 Diabetes
Status
Terminated
Phase
Not Applicable
Locations
United States
Study Type
Interventional
Intervention
Abbott Freestyle Libre Pro
LifeStyle
Sponsored by
About this trial
This is an interventional treatment trial for Type2 Diabetes focused on measuring Type 2 Diabetes, Hyperglycemia, Personal Nutrition Project
Eligibility Criteria
Inclusion Criteria:
- Age >21 years to <70 years
- Diagnosed with T2DM within 2 years with an HbA1c<7%
- Diabetes management by metformin or lifestyle intervention
- Fasting C-peptide ≥ 0.5 mg/mL (0.17 nmol/L) (to exclude those for whom hyperglycemic exposure is driven by β-cell failure rather than dietary behaviors, as well as those requiring escalation of the medication regime)
- Ownership a smart phone and are willing to use it to monitor multiple factors influencing glycemic response to glycemia (e.g., sleep, physical activity, diet, stress, medication, and hunger)
Exclusion Criteria:
- are unable or unwilling to provide informed consent;
- are unable to participate meaningfully in an intervention that involves self-monitoring using software available in English (e.g., due to uncorrected sight impairment, illiterate, non-English-speaking, dementia);
- are pregnant, are currently trying to become pregnant, or who become pregnant during the study
- are institutionalized (e.g., in a nursing home or personal care facility, or those who are incarcerated and have limited control over self-management)
- have had or are planning to have bariatric surgery during the study
- have a history of heart disease, kidney disease, or retinopathy (to rule-out those with long-standing, undiagnosed T2D)
- those with an active infection requiring antibiotics in the last 3 months or who develop an active infection requiring antibiotics during the study;
- those who use acetaminophen and are unwilling or unable to discontinue its use during the study (acetaminophen affects CGM accuracy)39
- immunosuppressive drugs within three months prior to participation and
- Chronically active inflammatory or neoplastic disease in the three years prior to enrollment.
- Patients with known food allergy.
Sites / Locations
- New York University School of Medicine
Arms of the Study
Arm 1
Arm 2
Arm Type
Active Comparator
Experimental
Arm Label
Life Style
Life Style + Metformin
Arm Description
Outcomes
Primary Outcome Measures
Observed Incremental Area Under the Curve (iAUCobs)
Observed incremental area under the curve (iAUCobs) at 2 hours following each meal and snack will be evaluated via CGM using the Abbott Freestyle Libre Pro, which captures interstitial glucose every 5 minutes. A sensor is inserted into the participant's upper arm. Participants will be blinded to glycemia tracings.
Secondary Outcome Measures
Full Information
1. Study Identification
Unique Protocol Identification Number
NCT03053518
Brief Title
Validation of Machine Learning Based Personalized Nutrition Algorithm to Reduce Postprandial Glycemic Excursions Among North American Individuals With Newly Diagnosed Type 2 Diabetes
Official Title
Validation of Machine Learning Based Personalized Nutrition Algorithm to Reduce Postprandial Glycemic Excursions Among North American Individuals With Newly Diagnosed Type 2 Diabetes
Study Type
Interventional
2. Study Status
Record Verification Date
August 2020
Overall Recruitment Status
Terminated
Why Stopped
Protocol Withdrawn
Study Start Date
June 30, 2017 (Actual)
Primary Completion Date
January 31, 2018 (Actual)
Study Completion Date
January 31, 2018 (Actual)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Sponsor
Name of the Sponsor
NYU Langone Health
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
Yes
Product Manufactured in and Exported from the U.S.
No
Data Monitoring Committee
No
5. Study Description
Brief Summary
This is an initial validation study of the Personal Nutrition Project (PNP) algorithm in a North American population with recently diagnosed Type 2 Diabetes (T2D). This is a 2-stage, single-group feeding study in 20 individuals, including 10 participants managed with lifestyle alone, and 10 managed with lifestyle plus metformin.
Detailed Description
The PNP algorithm, which uses a machine learning algorithm to predict postprandial glycemic, may be efficacious for generating tailored dietary advice to moderate the participant's glycemic response to food.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Type2 Diabetes
Keywords
Type 2 Diabetes, Hyperglycemia, Personal Nutrition Project
7. Study Design
Primary Purpose
Treatment
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Model Description
Investigators will recruit approximately 5 cohorts of 4 participants each for the sample size of 20 participants. A new cohort will be randomized approximately every 4 weeks. The maximum number of study participants at any point in the study will be 10.
Masking
None (Open Label)
Allocation
Non-Randomized
Enrollment
22 (Actual)
8. Arms, Groups, and Interventions
Arm Title
Life Style
Arm Type
Active Comparator
Arm Title
Life Style + Metformin
Arm Type
Experimental
Intervention Type
Device
Intervention Name(s)
Abbott Freestyle Libre Pro
Other Intervention Name(s)
Abbott
Intervention Description
A professional, blinded, continuous glucose monitoring device will be inserted on the back of the upper arm to measure interstitial glucose every 5 min for 4 times / day.
Intervention Type
Behavioral
Intervention Name(s)
LifeStyle
Intervention Description
Isocaloric diets (breakfast, lunch, dinner, and 2 snacks), which will be prepared and delivered daily, including 2 days each of low, moderate, and high glycemic load (GL) foods.
Primary Outcome Measure Information:
Title
Observed Incremental Area Under the Curve (iAUCobs)
Description
Observed incremental area under the curve (iAUCobs) at 2 hours following each meal and snack will be evaluated via CGM using the Abbott Freestyle Libre Pro, which captures interstitial glucose every 5 minutes. A sensor is inserted into the participant's upper arm. Participants will be blinded to glycemia tracings.
Time Frame
2 Hours
10. Eligibility
Sex
All
Minimum Age & Unit of Time
21 Years
Maximum Age & Unit of Time
70 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria:
Age >21 years to <70 years
Diagnosed with T2DM within 2 years with an HbA1c<7%
Diabetes management by metformin or lifestyle intervention
Fasting C-peptide ≥ 0.5 mg/mL (0.17 nmol/L) (to exclude those for whom hyperglycemic exposure is driven by β-cell failure rather than dietary behaviors, as well as those requiring escalation of the medication regime)
Ownership a smart phone and are willing to use it to monitor multiple factors influencing glycemic response to glycemia (e.g., sleep, physical activity, diet, stress, medication, and hunger)
Exclusion Criteria:
are unable or unwilling to provide informed consent;
are unable to participate meaningfully in an intervention that involves self-monitoring using software available in English (e.g., due to uncorrected sight impairment, illiterate, non-English-speaking, dementia);
are pregnant, are currently trying to become pregnant, or who become pregnant during the study
are institutionalized (e.g., in a nursing home or personal care facility, or those who are incarcerated and have limited control over self-management)
have had or are planning to have bariatric surgery during the study
have a history of heart disease, kidney disease, or retinopathy (to rule-out those with long-standing, undiagnosed T2D)
those with an active infection requiring antibiotics in the last 3 months or who develop an active infection requiring antibiotics during the study;
those who use acetaminophen and are unwilling or unable to discontinue its use during the study (acetaminophen affects CGM accuracy)39
immunosuppressive drugs within three months prior to participation and
Chronically active inflammatory or neoplastic disease in the three years prior to enrollment.
Patients with known food allergy.
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Mary Sevick, MD
Organizational Affiliation
NYU Langone Health
Official's Role
Principal Investigator
Facility Information:
Facility Name
New York University School of Medicine
City
New York
State/Province
New York
ZIP/Postal Code
10016
Country
United States
12. IPD Sharing Statement
Learn more about this trial
Validation of Machine Learning Based Personalized Nutrition Algorithm to Reduce Postprandial Glycemic Excursions Among North American Individuals With Newly Diagnosed Type 2 Diabetes
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