The HEADWIND Study - Part 4

Non-randomised, Controlled, Interventional Single-centre Study for the Design and Evaluation of an In-vehicle Hypoglycaemia Warning System in Diabetes The HEADWIND Study Part IV

To analyse driving behavior of individuals with type 1 diabetes in eu- and mild hypoglycaemia while driving in a real car. Based on the in-vehicle variables, the investigators aim at establishing algorithms capable of discriminating eu- and hypoglycaemic driving patterns using machine learning classifiers.

Study Overview

• Status: Completed
• Conditions: Diabetes; Diabetes Mellitus, Type 1
• Intervention / Treatment: Other: Controlled hypoglycaemic state while driving

Detailed Description

Hypoglycaemia is among the most relevant acute complications of diabetes mellitus. During hypoglycaemia physical, psychomotor, executive and cognitive function significantly deteriorate. These are important prerequisites for safe driving.

Accordingly, hypoglycaemia has consistently been shown to be associated with an increased risk of driving accidents and is, therefore, regarded as one of the relevant factors in traffic safety. Therefore, this study aims at evaluating a machine-learning based approach using in-vehicle data to detect hypoglycaemia during driving.

During controlled eu- and hypoglycaemia, participants with type 1 diabetes mellitus drive in a driving school car on a closed test-track while in-vehicle data is recorded. Based on this data, the investigators aim at building machine learning classifiers to detect hypoglycemia during driving.

• Study Type: Interventional
• Enrollment (Actual): 10
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Switzerland
  • Bern, Switzerland
    • University Department of Endocrinology, Diabetology, Clinical Nutrition and Metabolism

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 17 years to 56 years (Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• Informed consent as documented by signature
• Type 1 Diabetes mellitus as defined by WHO for at least 1 year or confirmed C-peptide negative (<100pmol/l with concomitant blood glucose >4 mmol/l)
• Age between 21-60 years
• HbA1c ≤ 9.0 %
• Functional insulin treatment with good knowledge of insulin self-management
• Passed driver's examination at least 3 years before study inclusion. Possession of a valid, definitive Swiss driver's license.
• Active driving in the last 6 months.

Exclusion Criteria:

• Contraindications to the drug used to induce hypoglycaemia (insulin aspart), known hypersensitivity or allergy to the adhesive patch used to attach the glucose sensor.
• Pregnancy or intention to become pregnant during the course of the study, lactating women or lack of safe contraception
• Other clinically significant concomitant disease states as judged by the investigator
• Physical or psychological disease likely to interfere with the normal conduct of the study and interpretation of the study results as judged by the investigator
• Renal failure
• Hepatic dysfunction
• Coronary heart disease
• Other cardiovascular disease
• Epilepsy
• Drug or alcohol abuse
• Inability to follow the procedures of the study, e.g. due to language problems, psychological disorders, dementia, etc. of the participant
• Participation in another study with an investigational drug within the 30 days preceding and during the present study
• Total daily insulin dose >2 IU/kg/day
• Specific concomitant therapy washout requirements prior to and/or during study participation
• Current treatment with drugs known to interfere with metabolism or driving performance

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm

Intervention / Treatment

Experimental: Intervention group

Other: Controlled hypoglycaemic state while driving; Participants will drive on a designated circuit with a real car on a test track accompanied by a driving instructor. Initially, a euglycaemic state (5.0 - 8.0 mmol/L) is established and blood glucose is then declined to hypoglycaemia (3.0 - 3.5 mmol/L) by administering insulin. Thereafter, blood glucose is raised again to euglycaemia (5.0 - 8.0mmol/L). During the procedure, driving data is recorded. Additionally, eye movement, head pose, facial expression, heart rate, skin conductance, and CGM values are recorded throughout the glycemic trajectory. Participants are blinded to the blood glucose values during the procedure.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Diagnostic accuracy of the hypoglycaemia warning system using in-vehicle data to detect hypoglycaemia quantified as the area under the receiver operating characteristics curve (AUROC).	The machine learning model is developed and evaluated based on in-vehicle data generated in eu- and hypoglycaemia. Detection performance of hypoglycaemia is quantified as AUROC.	240 minutes

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Diagnostic accuracy of the hypoglycaemia warning system using wearable data to detect hypoglycaemia quantified as the area under the receiver operating characteristics curve (AUROC).	The machine learning model is developed and evaluated based on wearable data recorded in eu- and hypoglycaemia. Detection performance of hypoglycemia is quantified as AUROC.	240 minutes
Diagnostic accuracy of the hypoglycaemia warning system using in-vehicle data and recordings of the continous glucose monitoring (CGM) system to detect hypoglycaemia quantified as sensitivity and specificity.	The CGM device is in use during controlled eu- and hypoglycaemia. Detection performance of hypoglycaemia is quantified as sensitivity and specificity.	240 minutes
Diagnostic accuracy of the hypoglycaemia warning system using wearable data and recordings of the CGM system to detect hypoglycaemia quantified as sensitivity and specificity.	The CGM device is in use during controlled eu- and hypoglycaemia. Detection performance of hypoglycaemia is quantified as sensitivity and specificity.	240 minutes
Change in driving features over the glycaemic trajectory.	Driving signals are recorded using a driving simulator.	240 minutes
Change of gaze coordinates over the glycaemic trajectory.	Gaze coordinates are recorded using an eye-tracker device.	240 minutes
Change of head pose over the glycaemic trajectory.	Head pose (position/rotation) is recorded using an eye-tracker device.	240 minutes
Change of heart rate over the glycaemic trajectory	Heart rate is recorded using a holter-ECG device and a wearable.	240 minutes
Change of heart rate variability over the glycaemic trajectory	Heart rate variability is recorded using a holter-ECG device and a wearable.	240 minutes
Change of electrodermal activity over the glycaemic trajectory	Electrodermal activity is recorded using a wearable.	240 minutes
Hypoglycaemic symptoms over the glycaemic trajectory.	Hypoglycemic symptoms are rated using a validated questionnaire (minimum score = 0, maximum score = 6, a higher score means more symptoms)	240 minutes
Change of cognitive performance over the glycaemic trajectory.	Cognitive performance will be assessed using the Trail Making B Test (lower time in seconds means better performance) and using the Digital Symbol Substitution Test (higher score means better performance).	240 minutes
Time course of the hormonal response over the glycaemic trajectory	Epinephrine, norepinephrine, glucagon, cortisol and growth hormone will be measured at pre-defined time points.	240 minutes
Self assessment of driving performance over the glycaemic trajectory.	Participants rate their driving performance on a 7-point Likert Scale (lower value means poorer driving performance).	240 minutes
Number of driving mishaps over the glycaemic trajectory.	Any driving mishaps, accidents and interventions by the driving instructor will be documented.	240 minutes
CGM accuracy over the glycaemic trajectory	CGM values will be recorded using a CGM sensor. Venous blood glucose is considered as the reference. Accuracy will be quantified using mean absolute relative difference (MARD) from the gold-standard and using the Clarke error grid.	240 minutes
Accuracy of our protocol to induce hypoglycaemia in achieving the intended hypoglycaemic range.	Accuracy will be quantified using mean absolute relative difference from the intended hypoglycaemic range.	240 minutes
Number of Adverse Events (AEs)	Adverse Events will be recorded at each study visit.	2 weeks, from screening to close out visit in each participant
Number of Serious Adverse Events (SAEs)	Serious Adverse Events will be recorded at each study visit.	2 weeks, from screening to close out visit in each participant
Emotional response to the hypoglycaemia warning system	Physiological response will be measured using an electro-dermal activity sensor (skin conductance) and eye tracker (eye blinks). Self-reported emotional response will be assessed with scales (e.g., valence, arousal, annoyance, sense of urgency).	240 minutes
Technology acceptance of the hypoglycaemia warning system	Technology acceptance will be measures with user experience questionnaires, such as the Unified Technology Acceptance and Use of Technology Questionnaire and free words associations.	240 minutes

Collaborators and Investigators

• Sponsor: University Hospital Inselspital, Berne
• Collaborators: Swiss Federal Institute of Technology; University of St.Gallen
• Investigators: Principal Investigator: Christoph Stettler, Prof. MD, Inselspital, Bern University Hospital, University of Bern, Switzerland, Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Bern, Switzerland

Study record dates

Study Major Dates

• Study Start (Actual): April 13, 2022
• Primary Completion (Actual): June 23, 2022
• Study Completion (Actual): June 23, 2022

Study Registration Dates

• First Submitted: March 24, 2022
• First Submitted That Met QC Criteria: March 24, 2022
• First Posted (Actual): April 1, 2022

Study Record Updates

• Last Update Posted (Actual): December 21, 2022
• Last Update Submitted That Met QC Criteria: December 20, 2022
• Last Verified: December 1, 2022

More Information

Terms related to this study

• Keywords: Hypoglycemia; Driving; Automotive Technology; Hypoglycaemia; Car
• Additional Relevant MeSH Terms: Glucose Metabolism Disorders; Metabolic Diseases; Immune System Diseases; Autoimmune Diseases; Endocrine System Diseases; Diabetes Mellitus; Diabetes Mellitus, Type 1; Hypoglycemia; Physiological Effects of Drugs; Hypoglycemic Agents
• Other Study ID Numbers: HEADWIND 4

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: Yes
• IPD Plan Description: Any requests for raw data will be reviewed by the HEADWIND scientific study board comprising the principal investigator (PI) and Co-PI as well as senior researchers leading the involved research groups at University Hospital Bern, Swiss Federal Institute of Technology (ETH) Zurich, and University of St. Gallen. Only applications for non-commercial use will be considered and should be sent to the PI. Applications should outline the purpose for the raw-data transfer. Any data that can be shared will need approval from the HEADWIND scientific study board and a Material Transfer Agreement in place. All data shared will be de-identified.
• IPD Sharing Access Criteria: Only applications for non-commercial use will be considered and should be sent to the PI.
• IPD Sharing Supporting Information Type: Analytic Code

Drug and device information, study documents

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