Ignite Creation Date:
2025-12-25 @ 4:07 AM
Ignite Modification Date:
2025-12-26 @ 3:03 AM
Study NCT ID:
NCT03414320
Status:
COMPLETED
Last Update Posted:
2018-08-02
First Post:
2018-01-12
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Proof of Concept - Identification of Patient-specific Parameters for Bolus Calculators for Type 1 Diabetes
Sponsor:
Universitaire Ziekenhuizen KU Leuven
Organization:
Study Overview
Official Title:
Proof of Concept Study for the Identification of Patient-specific Parameters for Bolus Calculators in Type 1 Diabetic Patients
Status:
COMPLETED
Status Verified Date:
2018-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
POC-IDENTITY-1
Brief Summary:
The adoption of bolus calculators has been limited by the slow speed of the current trial and error approach. The goal of this project is to automate the determination of patient specific insulin pump parameters based on current automatic electronic logbooks of glucose measurements, carbohydrate intake, and insulin usage, by means of a mathematical model. More specifically, the investigators are interested in computing the carbohydrate to insulin ratio (CIR) and insulin sensitivity factor (ISF), which are the main parameters of bolus calculators.
The present study is a proof-of-concept, open label, single arm clinical trial to validate the new method and refine both the mathematical model and the numerical techniques in well-regulated and disciplined type 1 diabetic subject.
The study is a "trial" of the selected underlying mathematical model and the associated algorithms to simulate the glucose values of a patient with uncertain meal-data.
The present study is a proof-of-concept, open label, single arm clinical trial to validate the new method and refine both the mathematical model and the numerical techniques in well-regulated and disciplined type 1 diabetic subject.
The study is a "trial" of the selected underlying mathematical model and the associated algorithms to simulate the glucose values of a patient with uncertain meal-data.
Detailed Description:
After signing informed consent and checking eligibility criteria participants will receive uniform education related to self-monitoring of blood glucose and continuous glucose monitoring (CGM) using the CGM sensor as well as on the bolus calculator (BC). The study will take three weeks (or three sensors) per patient.
Patients should live a close to normal life and should participate in their normal daily activities. During the study, patients must consequently keep using the BC of their insulin pump, record in the insulin pump when they eat extra food outside their regular meals and when they inject extra insulin without the use of their insulin pump. Faulty 'meal markers' have to be noted in a booklet and patients will also have to take pictures of their plate for each meal or record their meals in detail in a booklet. Patients should also consequently shut off insulin delivery when they disconnect their insulin pump and write it down in a booklet. The patients will be asked to wear an activity tracker (i.e. Fitbit), this data will help in the refinement of the model and will be used for research later in the same project.
During the study, patients must skip a total of three meals: breakfast, lunch and dinner (not on the same day, but within the three weeks). This gives the investigators a period of measurements in which they know that there are no significant amounts of unpredictable carbohydrates in the blood. Patients can give correction insulin or take extra fast carbohydrates to correct the glycaemia when needed and record this in the insulin pump or in a booklet. The fast rescue carbohydrates should be in the form of Dextro energy tablets (provided by the study team).
After the three weeks, patients will come back to the hospital where the study team will download data from the insulin pump, CGM sensor, and activity tracker. The booklet and photographs of the meals will be handed over to the study team. This is the end of the study for the patient. The collected patient data will further be used to assess the model fit of the chosen mathematical model as in, i.e. the investigators evaluate how well the model is able to reproduce the collected data.
Patients should live a close to normal life and should participate in their normal daily activities. During the study, patients must consequently keep using the BC of their insulin pump, record in the insulin pump when they eat extra food outside their regular meals and when they inject extra insulin without the use of their insulin pump. Faulty 'meal markers' have to be noted in a booklet and patients will also have to take pictures of their plate for each meal or record their meals in detail in a booklet. Patients should also consequently shut off insulin delivery when they disconnect their insulin pump and write it down in a booklet. The patients will be asked to wear an activity tracker (i.e. Fitbit), this data will help in the refinement of the model and will be used for research later in the same project.
During the study, patients must skip a total of three meals: breakfast, lunch and dinner (not on the same day, but within the three weeks). This gives the investigators a period of measurements in which they know that there are no significant amounts of unpredictable carbohydrates in the blood. Patients can give correction insulin or take extra fast carbohydrates to correct the glycaemia when needed and record this in the insulin pump or in a booklet. The fast rescue carbohydrates should be in the form of Dextro energy tablets (provided by the study team).
After the three weeks, patients will come back to the hospital where the study team will download data from the insulin pump, CGM sensor, and activity tracker. The booklet and photographs of the meals will be handed over to the study team. This is the end of the study for the patient. The collected patient data will further be used to assess the model fit of the chosen mathematical model as in, i.e. the investigators evaluate how well the model is able to reproduce the collected data.
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: