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

Clinical Trial ID: NCT03053518

Description

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.

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.


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.

  • Start Date

    2017-06-30

  • Last Updated

    2019-11-07

  • Sponsor

    NYU Langone Health

  • Condition Name

    Type2 Diabetes

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