Type 1 Diabetic Post Prandial Glycemia Evaluation Using an Algorithm

M-DT140 enrolled

Overview

The aim of this study is to demonstrate the efficacy of an algorithm to anticipate the post prandial glycemic profile in type I diabetic patient.

Study Type

OBSERVATIONAL

Enrollment

Conditions

Type I Diabetes

Interventions

Measure of glycemia levels and comparison to algorithm predictionsOTHER

The study aims to evaluate the efficacy of a new algorithm in predicting the evolution of glycemia levels after a full meal. Glycemia levels measured during and after a full meal will be compared to the values predicted by the algorithm. Composition of the meals will also be collected.

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: * Type 1 diabetes * ≥ 18 years old * Hb1Ac\<12% Exclusion Criteria: * Patient without continuous glucose monitoring system * Disease other than diabetes (bulimia, anorexia…) * Dialysis patient * Known history of drug or alcohol abuse * Patient under judicial protection * Person deprived of liberty * Pregnant, parturient or breastfeeding woman * Patient in psychiatric care * Patient admitted to a health or social institution for purposes other than research * Any reasons that might interfere with the evaluation of the study objectives

Locations (2)

APHM

Marseille, France

Hopital Sainte Musse

Toulon, France

Outcomes

Primary Outcomes

Algorithm efficacy

The Algorithm efficacy in predicting the risk or absence of risk of hyperglycemia two hours after taking a full meal is evaluated by comparing glycemic values calculated by the algorithm and those obtained using continuous glucose monitoring system measurements.

Time frame: 15 days

Secondary Outcomes

Algorithm efficacy (lower margin of error)

Time frame: 15 days

Algorithm efficacy versus meal composition

Meals will be analyzed within different groups according to their respective nutritional index. For each group, algorithm prediction reliability will be determined.

Time frame: 15 days

Influence of the age of the patients on algorithm results

The Algorithm efficacy will be analyzed according to the age of patients

Time frame: 15 days

Influence of the BMI on algorithms results

Weight and height of patients will be combined to report BMI in kg/m2. Algorithm efficacy will be analyzed according to the BMI of patients

Time frame: 15 days

Influence of the insulin administration on algorithm results

Data obtained from patients using insulin pumps will be compared to data obtained from patients using multiple daily insulin injections.

Time frame: 15 days

Data from ClinicalTrials.gov

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