Systematic Evaluation of Continuous Glucose Monitoring Data (SECOND)

Systematic Evaluation of Continuous Glucose Monitoring Data to for the Development of Clinical Solutions

This study retrospectively evaluates continuous glucose monitoring (CGM) and flash glucose monitoring (FGM) data and pursues two main objectives: First, the investigators analyze if glucose values are better controlled in the days directly before a consultation at our tertiary referral centre (so called "white coat adherence"). Second, the investigators use the collected CGM and FGM data to develop a hypoglycemia prediction model.

Study Overview

• Status: Completed
• Conditions: Diabetes Mellitus
• Intervention / Treatment: Behavioral: glucose control (Substudy A); Diagnostic test: hypoglycemia prediction (Substudy B)

Detailed Description

Substudy A.) Presence of white coat adherence in diabetic patients:

The investigators aim at evaluating the existence of a so called "white coat adherence" with regard to diabetes control, which means that blood-glucose is better controlled in the days immediately prior to a consultation at the diabetes clinic compared to the time-period further back. To analyse this phenomenon, the investigators use continuous glucose monitoring (CGM) and flash glucose monitoring (FGM) of diabetic patients and compare CGM-/FGM data of the last three days prior to the consultation with the CGM-/FGM data of the days 4-28 prior to the consultation, as well as the last seven days prior to the consultation with days 8-28 prior to the consultation.

Substudy B.) Retrospective data collection for the development and evaluation of a hypoglycemia prediction model:

Scope of the study is to use retrospective data for training and evaluation of a deep recurrent neural network based system for predicting the onset of hypoglycemic event at least 20 min ahead in time. The study aims to: I, assess the ability of deep learning algorithm to predict hypoglycemic events using the data collected during substudy 1. II, assess the ability of global model to be personalized using the data collected during sub-study 1. III, investigate the amount of "history" to be involved to achieve maximum performance in terms of prediction ability. IV, develop a global model, which can be easily further personalized to achieve optimum prediction performance per patient.

• Study Type: Observational
• Enrollment (Actual): 384

Contacts and Locations

Study Locations

• Switzerland
  • BE
    • Bern, BE, Switzerland, 3010
      • Inselspital, Bern University Hospital, University of Bern

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 16 years and older (Child, Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

All patients suffering from diabetes mellitus controlled at our tertiary referral centre using a CGM/FMG device for at least 50% of the time

Description

Inclusion Criteria:

• Diabetes mellitus
• CGM and/or FGM available for at least 50% of the time in last 4 weeks before consultation
• Written informed general consent for the retrospective analysis of data

Exclusion Criteria:

• Pregnancy

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

Diabetic patients using CGM/FGM; Evaluation of glucose control and application of hypoglycemia prediction models in diabetic patients wearing CGM and/or FGM devices for at least 50% of the time during the last 4 weeks prior to the medical consultation.

Behavioral: glucose control (Substudy A); Comparison of glucose values during days 0 - 3 with days 4 - 28 and 0 - 7 with days 8 - 28 before a medical consultation at the diabetes clinic in patients suffering from diabetes and wearing a continuous glucose monitoring and/or flash glucose monitoring device; Diagnostic test: hypoglycemia prediction (Substudy B); Use of CGM/FGM data to develop and evaluate a neural network based hypoglycemia prediction model

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change of time in target glucose range day 0-3 compared to day 4-28 and day 0-7 compared to day 8-28 prior to consultation (for Substudy A)	The time spent in the target glucose range from 3.9 to 10.0 mmol/l assessed by CGM/FGM.	01.01.2013 - 31.07.2018; outcome assessed at study end
Hypoglycemia prediction (for Substudy B)	Proportion of times a deep learning based algorithm can predict a hypoglycemic event (BG <4.0 mmol/l) at least 20 min ahead in time?	01.01.2013 - 31.07.2018; outcome assessed at study end

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change of time above and below glucose target range day 0-3 compared to day 4-28 and day 0-7 compared to day 8-28 prior to consultation (for Substudy A)	The time spent above and below the target glucose (3.9 to 10.0 mmol/l) assessed by CGM/FGM.	01.01.2013 - 31.07.2018; outcome assessed at study end
Change of average and standard deviation glucose day 0-3 compared to day 4-28 and day 0-7 compared to day 8-28 prior to consultation (for Substudy A)	Average and standard deviation glucose levels based on CGM/FGM data	01.01.2013 - 31.07.2018; outcome assessed at study end
Sensor wearing time day 0-3 compared to day 4-28 and day 0-7 compared to day 8-28 prior to consultation (for Substudy A)	Time CGM-/FGM sensor has been worn (%)	01.01.2013 - 31.07.2018; outcome assessed at study end
Change of coefficient of variation (CV) day 0-3 compared to day 4-28 and day 0-7 compared to day 8-28 prior to consultation (for Substudy A)	Coefficient of variation (CV) based on CGM/FGM data	01.01.2013 - 31.07.2018; outcome assessed at study end
Change of time in hypoglycemia day 0-3 compared to day 4-28 and day 0-7 compared to day 8-28 prior to consultation (for Substudy A)	The time with glucose levels < 3.0 based on CGM/FGM data	01.01.2013 - 31.07.2018; outcome assessed at study end
Change of time in hyperglycemia day 0-3 compared to day 4-28 and day 0-7 compared to day 8-28 prior to consultation (for Substudy A)	The time with glucose levels in the significant hyperglycaemia, as based on CGM/FGM (glucose levels > 13.9 mmol/l)	01.01.2013 - 31.07.2018; outcome assessed at study end
Change of mean amplitude of glucose excursion (MAGE) day 0-3 compared to day 4-28 and day 0-7 compared to day 8-28 prior to consultation (for Substudy A)	The mean amplitude of glucose excursion assessed by CGM/FGM	01.01.2013 - 31.07.2018; outcome assessed at study end

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change of total, basal and bolus insulin dose day 0-7 compared to day 8-28 prior to consultation (for Substudy A)	Total, basal and bolus insulin dose based on data of continuous subcutaneous insulin infusion data in patients treated with insulin pumps	01.01.2013 - 31.07.2018; outcome assessed at study end
Change of periods with glucose below 3.0mmol/l for at least 15 minutes day 0-3 compared to day 4-28 and day 0-7 compared to day 8-28 prior to consultation (for Substudy A)	Duration of periods when sensor glucose values was below 3.0mmol/l for at least 15 minutes	01.01.2013 - 31.07.2018; outcome assessed at study end
Change of periods with glucose above 13.9mmol/l for at least 15 minutes day 0-3 compared to day 4-28 and day 0-7 compared to day 8-28 prior to consultation (for Substudy A)	Duration of periods when sensor glucose values was above 13.9mmol/l for at least 15 minutes	01.01.2013 - 31.07.2018; outcome assessed at study end
Change of mean of daily differences (MODD) day 0-3 compared to day 4-28 and day 0-7 compared to day 8-28 prior to consultation (for Substudy A)	Mean of daily differences (MODD) based on CGM/FGM data	01.01.2013 - 31.07.2018; outcome assessed at study end

Collaborators and Investigators

• Sponsor: University Hospital Inselspital, Berne
• Investigators: Principal Investigator: Thomas Zueger, MD, Department of Diabetes, Endocrinology, Clinical Nutrition and Metabolism, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland; Study Director: Christoph Stettler, Prof., Department of Diabetes, Endocrinology, Clinical Nutrition and Metabolism, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland

Study record dates

Study Major Dates

• Study Start (Actual): April 1, 2018
• Primary Completion (Actual): July 19, 2019
• Study Completion (Actual): July 19, 2019

Study Registration Dates

• First Submitted: April 18, 2018
• First Submitted That Met QC Criteria: May 22, 2018
• First Posted (Actual): June 4, 2018

Study Record Updates

• Last Update Posted (Actual): August 13, 2019
• Last Update Submitted That Met QC Criteria: August 12, 2019
• Last Verified: August 1, 2019

More Information

Terms related to this study

• Keywords: continuous glucose monitoring; flash glucose monitoring; white coat adherence; hypoglycemia prediction; deep learning algorithm
• Other Study ID Numbers: 2018-00207

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No