Trials / Terminated
TerminatedNCT03053518
Validation of Machine Learning Based Personalized Nutrition Algorithm to Reduce Postprandial Glycemic Excursions Among North American Individuals With Newly Diagnosed Type 2 Diabetes
- Status
- Terminated
- Phase
- N/A
- Study type
- Interventional
- Enrollment
- 22 (actual)
- Sponsor
- NYU Langone Health · Academic / Other
- Sex
- All
- Age
- 21 Years – 70 Years
- Healthy volunteers
- Not accepted
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.
Conditions
Interventions
| Type | Name | Description |
|---|---|---|
| DEVICE | Abbott Freestyle Libre Pro | 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. |
| BEHAVIORAL | LifeStyle | 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. |
Timeline
- Start date
- 2017-06-30
- Primary completion
- 2018-01-31
- Completion
- 2018-01-31
- First posted
- 2017-02-15
- Last updated
- 2020-09-21
- Results posted
- 2020-09-21
Locations
1 site across 1 country: United States
Regulatory
- FDA-regulated device study
Source: ClinicalTrials.gov record NCT03053518. Inclusion in this directory is not an endorsement.