Type I Diabetes
Conditions
Keywords
Type I diabetes, Hyperglycemia, Post prandial glycemia, algorithm
Brief summary
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.
Interventions
OTHERMeasure of glycemia levels and comparison to algorithm predictions
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.
Sponsors
Centre Hospitalier Intercommunal de Toulon La Seyne sur Mer
Assistance Publique Hopitaux De Marseille
M-DT1
Study design
Observational model
OTHER
Time perspective
OTHER
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Algorithm efficacy | 15 days | 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. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Algorithm efficacy (lower margin of error) | 15 days | 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 (the accepted margin of error is reduced by 25 to 50% when compared with primary outcome). |
| Algorithm efficacy versus meal composition | 15 days | Meals will be analyzed within different groups according to their respective nutritional index. For each group, algorithm prediction reliability will be determined. |
| Influence of the age of the patients on algorithm results | 15 days | The Algorithm efficacy will be analyzed according to the age of patients |
| Influence of the BMI on algorithms results | 15 days | 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 |
| Influence of the insulin administration on algorithm results | 15 days | Data obtained from patients using insulin pumps will be compared to data obtained from patients using multiple daily insulin injections. |
Countries
France
Outcome results
None listed