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Validation of Machine Learning Based Personalized Nutrition Algorithm to Reduce Postprandial Glycemic Excursions Among North American Individuals With Newly Diagnosed Type 2 Diabetes

Not Applicable
Terminated
Conditions
Type2 Diabetes
Interventions
Device: Abbott Freestyle Libre Pro
Behavioral: LifeStyle
Registration Number
NCT03053518
Lead Sponsor
NYU Langone Health
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.

Recruitment & Eligibility

Status
TERMINATED
Sex
All
Target Recruitment
22
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)
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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.
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Study & Design

Study Type
INTERVENTIONAL
Study Design
PARALLEL
Arm && Interventions
GroupInterventionDescription
Life Style + MetforminAbbott Freestyle Libre Pro-
Life Style + MetforminLifeStyle-
Life StyleLifeStyle-
Primary Outcome Measures
NameTimeMethod
Observed Incremental Area Under the Curve (iAUCobs)2 Hours

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
NameTimeMethod

Trial Locations

Locations (1)

New York University School of Medicine

🇺🇸

New York, New York, United States

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