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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

NCT03053518 · Status: TERMINATED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 22

Last updated 2020-09-21

Study results available
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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.

Conditions

  • Type2 Diabetes

Interventions

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.

Sponsors & Collaborators

Principal Investigators

  • Mary Sevick, MD · NYU Langone Health

Study Design

Allocation
NON_RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
21 Years
Max Age
70 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2017-06-30
Primary Completion
2018-01-31
Completion
2018-01-31
FDA Device
Yes

Countries

  • United States

Study Locations

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Entities

Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT03053518 on ClinicalTrials.gov