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The HEADWIND Study - Part 2 (HEADWIND)

Primary Purpose

Diabetes, Diabetes Mellitus, Type 1

Status

Completed

Phase

Not Applicable

Locations

Switzerland

Study Type

Interventional

Intervention

Controlled hypoglycaemic state while driving

About this trial

This is an interventional other trial for Diabetes focused on measuring Automotive Technology, Hypoglycemia, Hypoglycaemia, Driving, Car

Eligibility Criteria

21 Years - 60 Years (Adult)All SexesDoes not accept healthy volunteers

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

Sites / Locations

Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism

Arms of the Study

Arm 1

Arm Type

Experimental

Arm Label

Intervention group

Arm Description

Outcomes

Primary Outcome Measures

Accuracy of the HEADWIND-model: Diagnostic accuracy of the hypoglycemia warning system (HEADWIND) in detecting hypoglycemia (blood glucose < 3.9 and < 3.0 mmol/l) quantified as the area under the receiver operator characteristics curve (AUC ROC).

Accuracy of the HEADWIND-model will be assessed using real car driving data recorded in progressive hypoglycemia and driving data will be analysed using applied machine learning technology for hypoglycemia detection.

Secondary Outcome Measures

Change of swerving

Change of swerving during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Change of spinning

Change of spinning during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Change of velocity

Change of velocity during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Change of steer

Change of steer during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Change of brake

Change of brake during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Change of steer torque

Change of steer torque during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Change of steer speed

Change of steer speed during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Defining the glycemic level when driving performance is decreased

Plasma-glucose level (mmol/L) when driving performance begins to be impaired will be assessed based on significantly altered driving parameters in serious hypoglycemia (< 3.0 mmol/L) compared to euglycemia (5.5mmol/L).

Driving performance before and after hypoglycemia based on driving parameters (swerving, spinning, velocity, steer, brake, steer torque, steer speed)

Based on significantly altered driving parameters in serious hypoglycemia (< 3.0 mmol/L) driving performance based on swerving, spinning, velocity, steer, brake, steer torque and steer speed, before and after hypoglycemia will be assessed

Change of heart-rate

Change of heart-rate during driving in hypoglycemia will be compared to euglycemia. Change of heart-rate will be measured with a holter-ecg and wearable devices.

Change of heart-rate variability

Change of heart-rate variability during driving in hypoglycemia will be compared to euglycemia. Heart-rate variability will be measured with a holter-ecg and wearable devices.

Change of electrodermal activity (EDA)

Change of EDA during driving in hypoglycemia will be compared to euglycemia. EDA will be measured with wearable devices.

Change of skin temperature

Change of skin temperature during driving in hypoglycemia will be compared to euglycemia. Change of skin temperature will be measured with wearable devices and a thermal camera.

Change of eye movement

Change of eye movement and gaze behaviour during driving in hypoglycemia will be compared to euglycemia. Eye movement of the participant will be recorded by a camera and an eye-tracker.

Change of facial expression

Change of facial expression during driving in hypoglycemia will be compared to euglycemia. Facial expression will be recorded by a camera.

Diagnostic accuracy in detecting hypoglycemia (blood glucose <3.9 mmol/l and <3.0 mmol/l) and hyperglycemia (blood glucose >13.9 mmol/l and >16.7 mmol/l) quantified as the area under the receiver operator characteristics curve using physiological data

Accuracy of dysglycemia detection using physiological data (heart-rate, heart-rate variability, skin temperature, EDA) recorded with wearable devices during the study period will be analysed using applied machine learning technology.

Diagnostic accuracy in detecting hypoglycemia (blood glucose < 3.9 mmol/l and < 3.0 mmol/l) quantified as the area under the receiver operator curve (AUC-ROC) using video data

Using video data recorded by a camera and a thermal camera accuracy in hypoglycaemia detection will be analysed with applied machine learning technology.

Diagnostic accuracy in detecting hypoglycemia (blood glucose < 3.9 mmol/l and < 3.0 mmol/l) quantified as the area under the receiver operator curve (AUC-ROC) using eye-tracking data

Using eye-tracking data recorded by a camera and an eye-tracker (to record gaze behaviour) accuracy in hypoglycemia detection will be analysed with applied machine learning technology.

CGM accuracy during the controlled hypoglycemic state

Accuracy (mean absolute relative difference, MARD) of CGM Sensor (Dexcom G6) in euglycemia (3.9 - 10 mmol/L), hypoglycemia (3.0 - 3.9mmol/L) and severe hypoglycemia (< 3.0 mmol/L) will be assessed based on plasma glucose measurements

CGM time-delay during the controlled hypoglycemic state

Time-delay (minutes) of CGM Sensor (Dexcom G6) during progressive hypoglycemia (hypoglycemic clamp) will be assessed compared to plasma glucose.

Change of glucagon

Change of glucagon before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), severe hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Change of growth hormone (GH)

Change of GH before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), severe hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Change of catecholamines

Change of catecholamines before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), severe hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Change of cortisol

Change of cortisol before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), severe hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Change of insulin

Insulin levels will be measured before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), serious hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Glycemic level at time point of hypoglycemia detection by the HEADWIND-model

Blood glucose at time point of hypoglycemia detection by the HEADWIND-model will be determined.

Comparison CGM and HEADWIND-model regarding time-point of hypoglycemia detection

Time point of hypoglycemia detection by CGM will be compared to time point of hypoglycemia detection by the HEADWIND-model.

Comparison CGM and HEADWIND-model regarding glycemia

Blood glucose at time point of hypoglycemia detection by the HEADWIND- model compared to glucose value of CGM at same time point will be assessed.

Accuracy-comparison of HEADWIND-model and HEADWINDplus-model

Diagnostic accuracy of the hypoglycaemia warning system (HEADWIND) to detect hypoglycaemia (blood glucose < 3.9 mmol/l and < 3.0 mmol/l) quantified as the area under the receiver operator characteristics curve (AUC ROC) using only driving parameters (HEADWIND-model) will be compared to the HEADWIND-model with the additional integration of physiological parameters, video and eye tracker data, in particular heart-rate, heart-rate variability, electrodermal activity (EDA), skin temperature and facial expression (HEADWINDplus-model)

Self-estimation of glucose and hypoglycemia

Evaluation of self-estimated glucose during progressive hypoglycemia and correlation with measured blood glucose.

Self-estimation of driving performance

Evaluation of self-estimated driving-performance in severe hypoglycemia (< 3.0 mmol/L) compared to euglycemia (5.5mmol/L). Self-estimated driving performance will be assessed on a absolute 7-point scale from 0-6 (a lower value means better outcome).

Time point of need-to-treat

Time point of self-perceived need-to-treat (hypoglycemia) compared to time point of hypoglycemia detection by the HEADWIND-model and CGM.

Self-perception of hypoglycemia symptoms

Correlation of perceived hypoglycemia symptoms on a scale from 0-6 (0 means better outcome) to measured blood glucose.

Self-perception of hypoglycemia symptoms compared to baseline hypoglycemia awareness

Correlation and comparison of perceived hypoglycemia symptoms on a scale from 0-6 (0 means better outcome) to baseline hypoglycemia awareness (Clarke-Score and Gold-Score, for both tests a score of higher or equal to 4 points indicates impaired awareness of hypoglycemia).

Driving mishaps and interventions by the driving instructor in euglycaemia (5-8 mmol/l), hypoglycaemia (< 3.9 mmol/l) and severe hypoglycaemia (< 3.0 mmol/l).

Driving mishaps and interventions will be assessed by the driving instructor using an assessment questionnaire with 4 questions on a 7 point Likert scale (lower value means worse outcome)

Direct comparison of driving performance scores assessed by the driving instructor in euglycemia (5-8 mmol/l), hypoglycaemia (<3.9 mmol/l) and severe hypoglycaemia (< 3.0 mmol/l)

Driving performance will be assessed by the driving instructor using an assessment questionnaire with a score from 1 to 7 (7 means the best outcome)

Incidence of Adverse Events (AEs)

Adverse Events will be recorded at each study visit.

Incidence of Serious Adverse Events (SAEs

Serious Adverse Events will be recorded at each study visit.

Pre-test perception of technology in general

Perception of technology in general will be assessed via questionnaire based self-reports (technology readiness index) measures on the 5-point Likert Scale ranging from "strongly disagree" to "strongly agree" with a scale ranging from -2 to 2 with higher values representing a better outcome (after inversion of negative items). The total score will be averaged across participants and used individually to support the interview responses when necessary.

Pre-test experience with in-vehicle voice assistants (IVAs) and technology in general

Pre-test experience with IVAs and technology in general will be assessed via questionnaire based self-reports (questionnaire of technology use and acceptance). The constructs Performance expectancy, Effort expectancy, Social influence, Facilitating conditions, Hedonic motivation, and Behavioural intention are measured on the 7-point Likert scale from "strongly disagree" to "strongly agree" with a scale range from -3 to 3 with higher values representing a better outcome. The construct Use is measured on the 7-point Likert scale ranging from "never" to "always" with a scale range from -3 to 3. The total score will be averaged per construct and across participants and used individually to support the interview responses when necessary.

Direct comparison between IVA's prompts and the behavioral responses

Direct comparison of conversational turns between IVA and patient during the ecological momentary assessment and the hypoglycaemia support.

Self-report of blood sugar level while driving (i.e. ecological momentary assessment)

Comparison of perceived blood sugar level to measured blood glucose, perceived blood sugar level between drives (see outcome 21), and baseline hypoglycemia awareness (Clarke-Score and Gold-Score, for both tests a score of higher or equal to 4 points indicates impaired awareness of hypoglycemia).

Comparison of cognitive trust in competence and session alliance with IVA to warning type

Cognitive trust in competence with IVA will be assessed via questionnaire based self-reports (Cognitive trust in competence construct from Trust and adoption of recommendations agents questionnaire), measured on the 7-point Likert scale from "strongly disagree" to "strongly agree" with a scale range from -3 to 3 and with higher values representing a better outcome. Session alliance with IVA will be assessed via questionnaire based self-reports (item from Session Alliance Inventory), measured on the 6-point Likert scale from "not at all" to "completely" with a scale range from 0 to 5 and with higher values representing a better outcome. The questionnaire will be submitted after delivering IVA's support intervention and will be compared with the type of warning delivered (i.e. disclosure vs no disclosure).

General user experience of the early hypoglycaemia warning system (EWS)

General user experience of the EWS will be assessed via questionnaire based self-reports (questionnaire for User experience questionnaire and van der Laan scale) measured on an analogue scale with adjective at its extremes (e.g. easy to learn-hard to learn, boring-exciting, good-bad, etc.) with a scale range from 0 to 100. The scores will be averaged for each scale across participants and used individually to support the interview responses when necessary.

Acceptance and use of the EWS

Acceptance and use of the EWS will be assessed via questionnaire based self-reports (questionnaire of technology use and acceptance) measured on the 7-point Likert scale from "strongly disagree" to "strongly agree" with a scale range from -3 to 3 with higher values representing a better outcome. The total score will be averaged per construct and across participants and used individually to support the interview responses when necessary.

Cognitive trust in competence and emotional trust in the recommendations from IVA

Cognitive trust in competence and emotional trust in the recommendations from IVA will be assessed via questionnaire based self-reports (Cognitive trust in competence and emotional trust constructs from Trust and adoption of recommendations agents questionnaire) measured on the 7-point Likert scale from "strongly disagree" to "strongly agree" with a scale range from -3 to 3 and with higher values representing a better outcome. The total score will be averaged per construct and across participants and used individually to support the interview responses when necessary

Perceived working alliance with IVA

Perceived working alliance with the IVA will be assessed via questionnaire based self-reports (session alliance inventory) measured on the 6-point Likert scale from "not at all" to "completely" with a scale range from 0 to 5 and with higher values representing a better outcome. The total score will be averaged per construct and across participants and used individually to support the interview responses when necessary

Full Information

NCT ID

NCT04569630

First Posted

September 17, 2020

Last Updated

June 28, 2021

Sponsor

Insel Gruppe AG, University Hospital Bern

Collaborators

ETH Zurich, University of St.Gallen

1. Study Identification

Unique Protocol Identification Number

NCT04569630

Brief Title

The HEADWIND Study - Part 2

Acronym

HEADWIND

Official Title

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 2

Study Type

Interventional

2. Study Status

Record Verification Date

June 2021

Overall Recruitment Status

Completed

Study Start Date

October 1, 2020 (Actual)

Primary Completion Date

May 27, 2021 (Actual)

Study Completion Date

May 28, 2021 (Actual)

3. Sponsor/Collaborators

Responsible Party, by Official Title

Sponsor

Name of the Sponsor

Insel Gruppe AG, University Hospital Bern

Collaborators

ETH Zurich, University of St.Gallen

4. Oversight

Studies a U.S. FDA-regulated Drug Product

Studies a U.S. FDA-regulated Device Product

5. Study Description

Brief Summary

To analyse driving behavior of individuals with type 1 diabetes in eu- and progressive hypoglycaemia while driving in a real car. Based on the driving variables provided by the car the investigators aim at establishing algorithms capable of discriminating eu- and hypoglycemic driving patterns using machine learning neural networks (deep machine learning classifiers).

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. Despite important developments in the field of diabetes technology, the problem of hypoglycaemia during driving persists. Automotive technology is highly dynamic, and fully autonomous driving might, in the end, resolve the issue of hypoglycemia-induced accidents. However, autonomous driving (level 4 or 5) is likely to be broadly available only to a substantially later time point than previously thought due to increasing concerns of safety associated with this technology. Therefore, solutions bridging the upcoming period by more rapidly and directly addressing the problem of hypoglycemia-associated traffic incidents are urgently needed. On the supposition that driving behaviour differs significantly between euglycaemic state and hypoglycaemic state, the investigators assume that different driving patterns in hypoglycemia compared to euglycemia can be used to generate hypoglycemia detection models using machine learning neural networks (deep machine learning classifiers).

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study

Diabetes, Diabetes Mellitus, Type 1

Keywords

Automotive Technology, Hypoglycemia, Hypoglycaemia, Driving, Car

7. Study Design

Primary Purpose

Other

Study Phase

Not Applicable

Interventional Study Model

Single Group Assignment

Masking

None (Open Label)

Allocation

N/A

Enrollment

22 (Actual)

8. Arms, Groups, and Interventions

Arm Title

Intervention group

Arm Type

Experimental

Intervention Type

Other

Intervention Name(s)

Controlled hypoglycaemic state while driving

Intervention Description

Participants will drive on a designated circuit with a real car on a test track accompanied by a driving instructor. Driving data will be recorded in 4 subsequent glycemic states using an adapted hypoglycemic clamp protocol: euglycemia (d1, 5-8 mmol/l), progressive hypoglycaemia (d2, declining from 4.5 to 2.5 mmol/l), stable hypoglycemia (d3, 2.0-2.5 mmol/l), and again in euglycaemia (d4, 5-8 mmol/l). Patients will be blinded to their glucose levels.

Primary Outcome Measure Information:

Title

Description

Time Frame

240 minutes

Secondary Outcome Measure Information:

Title

Change of swerving

Description

Change of swerving during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Time Frame

240 minutes

Title

Change of spinning

Description

Change of spinning during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Time Frame

240 minutes

Title

Change of velocity

Description

Change of velocity during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Time Frame

240 minutes

Title

Change of steer

Description

Change of steer during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Time Frame

240 minutes

Title

Change of brake

Description

Change of brake during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Time Frame

240 minutes

Title

Change of steer torque

Description

Change of steer torque during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Time Frame

240 minutes

Title

Change of steer speed

Description

Change of steer speed during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Time Frame

240 minutes

Title

Defining the glycemic level when driving performance is decreased

Description

Time Frame

240 minutes

Title

Driving performance before and after hypoglycemia based on driving parameters (swerving, spinning, velocity, steer, brake, steer torque, steer speed)

Description

Time Frame

240 minutes

Title

Change of heart-rate

Description

Change of heart-rate during driving in hypoglycemia will be compared to euglycemia. Change of heart-rate will be measured with a holter-ecg and wearable devices.

Time Frame

240 minutes

Title

Change of heart-rate variability

Description

Change of heart-rate variability during driving in hypoglycemia will be compared to euglycemia. Heart-rate variability will be measured with a holter-ecg and wearable devices.

Time Frame

240 minutes

Title

Change of electrodermal activity (EDA)

Description

Change of EDA during driving in hypoglycemia will be compared to euglycemia. EDA will be measured with wearable devices.

Time Frame

240 minutes

Title

Change of skin temperature

Description

Change of skin temperature during driving in hypoglycemia will be compared to euglycemia. Change of skin temperature will be measured with wearable devices and a thermal camera.

Time Frame

240 minutes

Title

Change of eye movement

Description

Change of eye movement and gaze behaviour during driving in hypoglycemia will be compared to euglycemia. Eye movement of the participant will be recorded by a camera and an eye-tracker.

Time Frame

240 minutes

Title

Change of facial expression

Description

Change of facial expression during driving in hypoglycemia will be compared to euglycemia. Facial expression will be recorded by a camera.

Time Frame

240 minutes

Title

Description

Time Frame

Throughout the study, expected to be up to 12 months

Title

Diagnostic accuracy in detecting hypoglycemia (blood glucose < 3.9 mmol/l and < 3.0 mmol/l) quantified as the area under the receiver operator curve (AUC-ROC) using video data

Description

Using video data recorded by a camera and a thermal camera accuracy in hypoglycaemia detection will be analysed with applied machine learning technology.

Time Frame

Throughout the study, expected to be up to 12 months

Title

Diagnostic accuracy in detecting hypoglycemia (blood glucose < 3.9 mmol/l and < 3.0 mmol/l) quantified as the area under the receiver operator curve (AUC-ROC) using eye-tracking data

Description

Using eye-tracking data recorded by a camera and an eye-tracker (to record gaze behaviour) accuracy in hypoglycemia detection will be analysed with applied machine learning technology.

Time Frame

Throughout the study, expected to be up to 12 months

Title

CGM accuracy during the controlled hypoglycemic state

Description

Time Frame

240 minutes

Title

CGM time-delay during the controlled hypoglycemic state

Description

Time-delay (minutes) of CGM Sensor (Dexcom G6) during progressive hypoglycemia (hypoglycemic clamp) will be assessed compared to plasma glucose.

Time Frame

240 minutes

Title

Change of glucagon

Description

Change of glucagon before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), severe hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Time Frame

240 minutes

Title

Change of growth hormone (GH)

Description

Change of GH before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), severe hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Time Frame

240 minutes

Title

Change of catecholamines

Description

Change of catecholamines before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), severe hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Time Frame

240 minutes

Title

Change of cortisol

Description

Change of cortisol before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), severe hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Time Frame

240 minutes

Title

Change of insulin

Description

Insulin levels will be measured before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), serious hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Time Frame

240 minutes

Title

Glycemic level at time point of hypoglycemia detection by the HEADWIND-model

Description

Blood glucose at time point of hypoglycemia detection by the HEADWIND-model will be determined.

Time Frame

240 minutes

Title

Comparison CGM and HEADWIND-model regarding time-point of hypoglycemia detection

Description

Time point of hypoglycemia detection by CGM will be compared to time point of hypoglycemia detection by the HEADWIND-model.

Time Frame

240 minutes

Title

Comparison CGM and HEADWIND-model regarding glycemia

Description

Blood glucose at time point of hypoglycemia detection by the HEADWIND- model compared to glucose value of CGM at same time point will be assessed.

Time Frame

240 minutes

Title

Accuracy-comparison of HEADWIND-model and HEADWINDplus-model

Description

Time Frame

240 minutes

Title

Self-estimation of glucose and hypoglycemia

Description

Evaluation of self-estimated glucose during progressive hypoglycemia and correlation with measured blood glucose.

Time Frame

240 minutes

Title

Self-estimation of driving performance

Description

Time Frame

240 minutes

Title

Time point of need-to-treat

Description

Time point of self-perceived need-to-treat (hypoglycemia) compared to time point of hypoglycemia detection by the HEADWIND-model and CGM.

Time Frame

240 minutes

Title

Self-perception of hypoglycemia symptoms

Description

Correlation of perceived hypoglycemia symptoms on a scale from 0-6 (0 means better outcome) to measured blood glucose.

Time Frame

240 minutes

Title

Self-perception of hypoglycemia symptoms compared to baseline hypoglycemia awareness

Description

Time Frame

240 minutes

Title

Driving mishaps and interventions by the driving instructor in euglycaemia (5-8 mmol/l), hypoglycaemia (< 3.9 mmol/l) and severe hypoglycaemia (< 3.0 mmol/l).

Description

Driving mishaps and interventions will be assessed by the driving instructor using an assessment questionnaire with 4 questions on a 7 point Likert scale (lower value means worse outcome)

Time Frame

240 minutes

Title

Direct comparison of driving performance scores assessed by the driving instructor in euglycemia (5-8 mmol/l), hypoglycaemia (<3.9 mmol/l) and severe hypoglycaemia (< 3.0 mmol/l)

Description

Driving performance will be assessed by the driving instructor using an assessment questionnaire with a score from 1 to 7 (7 means the best outcome)

Time Frame

240 minutes

Title

Incidence of Adverse Events (AEs)

Description

Adverse Events will be recorded at each study visit.

Time Frame

Throughout the study, expected to be up to 12 months

Title

Incidence of Serious Adverse Events (SAEs

Description

Serious Adverse Events will be recorded at each study visit.

Time Frame

Throughout the study, expected to be up to 12 months

Title

Pre-test perception of technology in general

Description

Time Frame

Throughout the study, expected to be up to 12 months

Title

Pre-test experience with in-vehicle voice assistants (IVAs) and technology in general

Description

Time Frame

Throughout the study, expected to be up to 12 months

Title

Direct comparison between IVA's prompts and the behavioral responses

Description

Direct comparison of conversational turns between IVA and patient during the ecological momentary assessment and the hypoglycaemia support.

Time Frame

240 minutes

Title

Self-report of blood sugar level while driving (i.e. ecological momentary assessment)

Description

Time Frame

240 minutes

Title

Comparison of cognitive trust in competence and session alliance with IVA to warning type

Description

Time Frame

240 minutes

Title

General user experience of the early hypoglycaemia warning system (EWS)

Description

Time Frame

Throughout the study, expected to be up to 12 months

Title

Acceptance and use of the EWS

Description

Time Frame

Throughout the study, expected to be up to 12 months

Title

Cognitive trust in competence and emotional trust in the recommendations from IVA

Description

Time Frame

Throughout the study, expected to be up to 12 months

Title

Perceived working alliance with IVA

Description

Time Frame

Throughout the study, expected to be up to 12 months

10. Eligibility

Sex

All

Minimum Age & Unit of Time

21 Years

Maximum Age & Unit of Time

60 Years

Accepts Healthy Volunteers

Eligibility Criteria

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

Overall Study Officials:

First Name & Middle Initial & Last Name & Degree

Christoph Stettler, Prof. MD

Organizational Affiliation

Inselspital, Bern University Hospital, University of Bern

Official's Role

Principal Investigator

Facility Information:

Facility Name

Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism

City

Bern

Country

Switzerland

12. IPD Sharing Statement

Learn more about this trial

The HEADWIND Study - Part 2

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