Metabolic DiseaseNCT05461144
AI Models for Non-invasive Glycaemic Event Detection Using ECG in Type 1 Diabetics
An observational study of Metabolic Disease, run by University Hospitals Coventry and Warwickshire NHS Trust.
Trial summary
This observational study aims to recruit up to thirty T1DM patients from a diabetic outpatient clinic at the University Hospital Coventry and Warwickshire for a two-phase study. The first phase involves attending an inpatient protocol for up to thirty-six hours in a calorimetry room at the Human Metabolism Research… Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Metabolic Disease
- How many people
- 30 participants
- Where
- No sites listed yet
- Study dates
- 30 Sep 2022to 1 May 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: The population will be recruited from the Warwickshire Institute for the study of diabetes, Endocrinology and Metabolism, at the University Hospitals Coventry and Warwickshire. WISDEM is a flagship partnership between the hospitals and the University of Warwick Medical School created to tackle diabetes and related metabolic conditions.
Who may be able to join
- The study will be open to all individuals living independently, over 18 years without acute illness or ongoing clinical investigation, or volunteers with a stable medical condition may be included. Volunteers with an ongoing medical condition will only be included after detailed consultation with our clinical and dietetics members of the team; however, it is imperative that volunteers are able to provide written informed consent.
Who cannot join
- Whilst the study employs a deliberately open inclusion criterion, the following exclusion measures will be employed:
- Children (under 18 yrs)
- Any adult who lacks decisional capacity
- Claustrophobia, isolophobia, recent abnormal exercise, radiation exposure within the preceding 24 hours of entering the whole-body calorimeter and feeling unwell in any way.
- Needle phobia
- Any medical/endocrine problem that could affect energy expenditure (e.g. thyroid problems, Cushing's syndrome)
Show all 10Show fewer
- Chronic inflammatory disorders like rheumatoid arthritis, or long term use of steroids or other immunomodulators like cyclosporine, azathioprine.
- Beta blockers
- Currently actively losing weight
- Depression or any psychiatric illness
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
Official title: Development and Validation of Artificial Intelligence Models for Non-invasive Glycaemic Event Detection Using ECG in Type 1 Diabetics
This observational study aims to recruit up to thirty T1DM patients from a diabetic outpatient clinic at the University Hospital Coventry and Warwickshire for a two-phase study. The first phase involves attending an inpatient protocol for up to thirty-six hours in a calorimetry room at the Human Metabolism Research Unit under controlled conditions, followed by a phase of free-living, for up to three days, in which participants will go about their normal daily activities without restriction. Throughout the study, the participants will wear commercially available wearable sensors to measure and record physiological signals (e.g., electrocardiogram and continuous glucose monitor). Data collected will be used to develop and validate an AI model using state-of-the-art deep-learning methods for the purpose of non-invasive glycaemic event detection.
Read the detailed description
The study volunteers will be asked to an attend an 'inpatient' facility for up to 36 hrs dedicated to advanced metabolic measurement (HMRU). They will be asked to consume prepared meals of varying macronutrient content as part of a balanced diet, and performed prescribed physical activity. During this time the volunteers will be measured by instrumentation which will investigate the chemical concentration in respired gases (e.g. whole-body calorimeters, metabolic carts); bloods, saliva and urine samples will be taken. If the participant then wishes, we will ask them to continue to wear the wearable devices in a home setting for a maximum one week.
The data derived from this study will allow new tools and mathematical models to be developed that can be used to analyse and simulate patient metabolic response. It is envisaged this study will give further evidence to support future research into glucose utilisation in diseased metabolic populations.
- Conditions
- Metabolic Disease
- Keywords
- Endochrine
- Medical subject headings
- Metabolic Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Type1diabetes patients | Males and females diagnosed with T1D, aged over 18 years old who are currently under the care of the Warwickshire Institute for the Study of Diabetes, Endocrinolgy and Metabolism (WISDEM) at the University Hospitals Coventry and Warwickshire. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Interstitial Glucose
As measured by a continuous glucose monitor [NOTE] Observational study thus a key measurement not a true outcome measure.
Measured: For the duration of the study, up to 5 days
Secondary outcomes (4)
ECG -Interval across different fiducial points
As measured by an ambulatory ECG device [NOTE] Observational study thus a key measurement not a true outcome measure.
The interval across different fiducial points (P.Q.R,S,T) is one of the features that are useful to quantify the difference in ECG signals for different glycaemic events.
Measured: For the duration of the study, up to 5 days
ECG - Slope across different fiducial points
As measured by an ambulatory ECG device [NOTE] Observational study thus a key measurement not a true outcome measure.
The Slope across different fiducial points (P.Q.R,S,T) is one of the features that are useful to quantify the difference in ECG signals for different glycaemic events.
Measured: For the duration of the study, up to 5 days
ECG - Indices of Heart Rate Variability
As measured by an ambulatory ECG device [NOTE] Observational study thus a key measurement not a true outcome measure.
Heart rate variability (HRV) is the fluctuation in the time intervals between adjacent heartbeats. There are several indices that are useful to quantify the difference in ECG signals for different glycaemic events such as Ultra Low Frequency (ULF) (≤0.003 Hz), Very Low Frequency (VLF) (0.0033-0.04 Hz), Low Frequency (LF) (0.04-0.15 Hz) and High Frequency (HF) (0.15-0.4 Hz)
Measured: For the duration of the study, up to 5 days
Blood Pressure (Systolic and Diastolic)
As measured by an ambulatory blood pressure device [NOTE] Observational study thus a key measurement not a true outcome measure.
Measured: For the duration of the study, up to 5 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Jul 2022
- Study start30 Sep 2022 (estimated)
- Primary completion1 May 2026 (estimated)
- Study completion1 May 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Metabolic DiseaseStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 30 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University Hospitals Coventry and Warwickshire NHS Trust
- Sponsor type
- University, hospital or other
- Collaborators
- University of Warwick
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05461144
- Sponsor's protocol ID
- JH206817a
- Status last verified
- Jul 2022
- First submitted
- 24 Jun 2022
- Last updated
- 15 Jul 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Porumb M, Stranges S, Pescape A, Pecchia L. Precision Medicine and Artificial Intelligence: A Pilot Study on Deep Learning for Hypoglycemic Events Detection based on ECG. Sci Rep. 2020 Jan 13;10(1):170. doi: 10.1038/s41598-019-56927-5.
PubMed 31932608Porumb M, Griffen C, Hattersley J, Pecchia L. Nocturnal low glucose detection in healthy elderly from one-lead ECG using convolutional denoising autoencoders. Biomedical Signal Processing and Control. 2020;62:102054.
Cisuelo O, Stokes K, Oronti IB, Haleem MS, Barber TM, Weickert MO, Pecchia L, Hattersley J. Development of an artificial intelligence system to identify hypoglycaemia via ECG in adults with type 1 diabetes: protocol for data collection under controlled and free-living conditions. BMJ Open. 2023 Apr 18;13(4):e067899. doi: 10.1136/bmjopen-2022-067899.
PubMed 37072364
Study at a glance
From the registry record, last updated by the sponsor on 15 Jul 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development and Validation of Artificial Intelligence Models for Non-invasive Glycaemic Event Detection Using ECG in Type 1 Diabetics
- ClinicalTrials.gov ID
- NCT05461144
- Acronym / sponsor ID
- JH206817a
- Conditions
- Metabolic Disease
- Keywords
- Endochrine
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 30 participants (estimated)
- Lead sponsor
- University Hospitals Coventry and Warwickshire NHS TrustUniversity, hospital or other
- Collaborators
- University of Warwick
- Study start
- 30 Sep 2022 (estimated)
- Primary completion
- 1 May 2026 (estimated)
- Study completion
- 1 May 2027 (estimated)
- First posted
- 15 Jul 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This observational study aims to recruit up to thirty T1DM patients from a diabetic outpatient clinic at the University Hospital Coventry and Warwickshire for a two-phase study. The first phase involves attending an inpatient protocol for up to thirty-six hours in a calorimetry room at the Human Metabolism Research Unit under controlled conditions, followed by a phase of free-living, for up to three days, in which participants will go about their normal daily activities without restriction. Throughout the study, the participants will wear commercially available wearable sensors to measure and record physiological signals (e.g., electrocardiogram and continuous glucose monitor). Data collected will be used to develop and validate an AI model using state-of-the-art deep-learning methods for the purpose of non-invasive glycaemic event detection.
Detailed description
The study volunteers will be asked to an attend an 'inpatient' facility for up to 36 hrs dedicated to advanced metabolic measurement (HMRU). They will be asked to consume prepared meals of varying macronutrient content as part of a balanced diet, and performed prescribed physical activity. During this time the volunteers will be measured by instrumentation which will investigate the chemical concentration in respired gases (e.g. whole-body calorimeters, metabolic carts); bloods, saliva and urine samples will be taken. If the participant then wishes, we will ask them to continue to wear the wearable devices in a home setting for a maximum one week.
The data derived from this study will allow new tools and mathematical models to be developed that can be used to analyse and simulate patient metabolic response. It is envisaged this study will give further evidence to support future research into glucose utilisation in diseased metabolic populations.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Type1diabetes patients | – | –Males and females diagnosed with T1D, aged over 18 years old who are currently under the care of the Warwickshire Institute for the Study of Diabetes, Endocrinolgy and Metabolism (WISDEM) at the University Hospitals Coventry and Warwickshire. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- The population will be recruited from the Warwickshire Institute for the study of diabetes, Endocrinology and Metabolism, at the University Hospitals Coventry and Warwickshire. WISDEM is a flagship partnership between the hospitals and the University of Warwick Medical School created to tackle diabetes and related metabolic conditions.
Key inclusion criteria (1 listed)
- The study will be open to all individuals living independently, over 18 years without acute illness or ongoing clinical investigation, or volunteers with a stable medical condition may be included. Volunteers with an ongoing medical condition will only be included after detailed consultation with our clinical and dietetics members of the team; however, it is imperative that volunteers are able to provide written informed consent.
Key exclusion criteria (10 listed)
- Whilst the study employs a deliberately open inclusion criterion, the following exclusion measures will be employed:
- Children (under 18 yrs)
- Any adult who lacks decisional capacity
- Claustrophobia, isolophobia, recent abnormal exercise, radiation exposure within the preceding 24 hours of entering the whole-body calorimeter and feeling unwell in any way.
- Needle phobia
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Interstitial Glucose
Time frame: For the duration of the study, up to 5 days
As measured by a continuous glucose monitor [NOTE] Observational study thus a key measurement not a true outcome measure.
4 secondary outcomes
ECG -Interval across different fiducial points
Time frame: For the duration of the study, up to 5 days
ECG - Slope across different fiducial points
Time frame: For the duration of the study, up to 5 days
ECG - Indices of Heart Rate Variability
Time frame: For the duration of the study, up to 5 days
Blood Pressure (Systolic and Diastolic)
Time frame: For the duration of the study, up to 5 days
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Jul 2022.
- Background: PubMed 31932608Porumb M, Stranges S, Pescape A, Pecchia L. Precision Medicine and Artificial Intelligence: A Pilot Study on Deep Learning for Hypoglycemic Events Detection based on ECG. Sci Rep. 2020 Jan 13;10(1):170. doi: 10.1038/s41598-019-56927-5.
- BackgroundPorumb M, Griffen C, Hattersley J, Pecchia L. Nocturnal low glucose detection in healthy elderly from one-lead ECG using convolutional denoising autoencoders. Biomedical Signal Processing and Control. 2020;62:102054.
- Derived from this study: PubMed 37072364Cisuelo O, Stokes K, Oronti IB, Haleem MS, Barber TM, Weickert MO, Pecchia L, Hattersley J. Development of an artificial intelligence system to identify hypoglycaemia via ECG in adults with type 1 diabetes: protocol for data collection under controlled and free-living conditions. BMJ Open. 2023 Apr 18;13(4):e067899. doi: 10.1136/bmjopen-2022-067899.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Questions about this trial
What is this clinical trial studying?
An observational study of Metabolic Disease, run by University Hospitals Coventry and Warwickshire NHS Trust.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 10 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 15 Jul 2022. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact John G Hattersley, PhD (+44 (0) 24 7696 6068, john.hattersley@uhcw.nhs.uk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Interstitial Glucose (time frame: For the duration of the study, up to 5 days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05461144, which also lists 3 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 Jul 2022.