Prediction of Blood Pressure, Glycated Haemoglobin and Estimated Glomerular Filtration Rate From Digital Retinal ImagesNCT04814680
Machine-Learning Algorithm for Prediction of Blood Pressure, Glycated Haemoglobin and Estimated Glomerular Filtration Rate
An observational study of Prediction of Blood Pressure, Glycated Haemoglobin and Estimated Glomerular Filtration Rate From Digital Retinal Images, run by AstraZeneca at 2 sites in Kenya.
Trial summary
This is a non-interventional pilot study with the following objectives: Establish scalable methodology for collection of retinal images, blood pressure (BP) and laboratory-based assessments Compare the results of a machine-learning algorithm in predicting BP, glycated haemoglobin (HbA1c) and estimated glomerular… Read more about this study
- Who is it for?
- Ages 35 to 130 years
- Conditions the study is for
- Prediction of Blood Pressure, Glycated Haemoglobin and Estimated Glomerular Filtration Rate From Digital Retinal Images
- How many people
- 301 participants
- Where
- 2 sitesKenya
- Study dates
- 8 Nov 2021to 10 Feb 2022
- Phase
- Observational
- Are there results?
- None posted in the registry
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 35 to 130 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Participants have to be more than 35 years, able to provide written consent and meet the following inclusion criteria: * With or without DM (at least 50% of participants will have an HbA1c ≥ 6.5%* and/or a known diagnosis of DM) * Male or female (at least 40% of participants must be male, and at least 40% must be female)
Who may be able to join
- Participant must be ≥ 35 years of age, at the time of signing the informed consent.
- With or without DM (at least 50% of participants will have an HbA1c ≥ 6.5%* and/or a known diagnosis of DM)
- Male or female (at least 40% of participants must be male, and at least 40% must be female)
- Capable of giving signed informed consent as described in Appendix A
Who cannot join
- As judged by the investigator, any evidence of a medical condition which in the investigator's opinion makes it undesirable for the participant to participate in the study for example, but not limited to, if a participant is critically unwell or requiring ongoing emergency treatment
- Any known eye condition that may preclude clear imaging of the retina for example; cataracts
- Involvement in the planning and/or conduct of the study (applies to both AstraZeneca staff and/or staff at the study site).
- Judgment by the investigator that the participant should not participate in the study if the participant is unlikely to comply with study procedures, restrictions and requirements.
- Previous enrolment in the present study with the exception of roll-in participants who may be re-screened and re-enrolled.
Trial locations and contacts
2 sites in 1 country.
About this study
Official title: A Non-Interventional Pilot Study to Evaluate A Machine-Learning Algorithm for Prediction of Blood Pressure, Glycated Haemoglobin and Estimated Glomerular Filtration Rate From Digital Retinal Images
This is a non-interventional pilot study with the following objectives:
- Establish scalable methodology for collection of retinal images, blood pressure (BP) and laboratory-based assessments
- Compare the results of a machine-learning algorithm in predicting BP, glycated haemoglobin (HbA1c) and estimated glomerular filtration rate (eGFR) from digital retinal images with clinical and laboratory-based measures
- Determine the required sample size needed to support a future study to fully validate the machine-learning algorithm
- Keywords
- - Machine learning; retinal images; blood pressure; glycated haemoglobin; glomerular filtration rate
What is being measured
The primary outcome is the main question the study is designed to answer.
To assess successful use of methodology for retinal image acquisition, BP (ABPM or manual), HbA1C (laboratory based or point of care test) and e-GFR measurement.
Proportion of participants with completed study procedures and interpretable results including both retinal images, systolic and diastolic BP (ABPM or manual), HbA1c (laboratory based or point of care test) and eGFR at Visit 1
Measured: up to 66 day
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Mar 2021
- Study start8 Nov 2021
- Primary completion10 Feb 2022
- Study completion10 Feb 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Prediction of Blood Pressure, Glycated Haemoglobin and Estimated Glomerular Filtration Rate From Digital Retinal ImagesStudies of the same condition, open and under way.
- More trials run by AstraZenecaThe sponsor's other registered studies.
- 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
- Case only
- Time perspective
- Prospective
- Enrolment
- 301 participants (actual)
Sponsor and investigators
- Lead sponsor
- AstraZeneca
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- IQVIA Pty Ltd
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04814680
- Sponsor's protocol ID
- D9080C00001
- Status last verified
- Dec 2022
- First submitted
- 23 Mar 2021
- Last updated
- 4 Jan 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Qualified researchers can request access to anonymized individual patient-level data from AstraZeneca group of companies sponsored clinical trials via the request portal. All request will be evaluated as per the AZ disclosure commitment: https://astrazenecagrouptrials.pharmacm.com/ST/Submission/Disclosure.
Publications
White T, Selvarajah V, Wolfhagen-Sand F, Svangard N, Mohankumar G, Fenici P, Rough K, Onyango N, Lyons K, Mack C, Nduba V, Noorali Saleh M, Abayo I, Siddiqui A, Majdanska-Strzalka M, Kaszubska K, Hegelund-Myrback T, Esterline R, Manzur A, Parker VER. Prediction of cardiovascular risk factors from retinal fundus photographs: Validation of a deep learning algorithm in a prospective non-interventional study in Kenya. Diabetes Obes Metab. 2024 Jul;26(7):2722-2731. doi: 10.1111/dom.15587. Epub 2024 Apr 15.
PubMed 38618987
Study at a glance
From the registry record, last updated by the sponsor on 4 Jan 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Non-Interventional Pilot Study to Evaluate A Machine-Learning Algorithm for Prediction of Blood Pressure, Glycated Haemoglobin and Estimated Glomerular Filtration Rate From Digital Retinal Images
- ClinicalTrials.gov ID
- NCT04814680
- Acronym / sponsor ID
- D9080C00001
- Keywords
- - Machine learning; retinal images; blood pressure; glycated haemoglobin; glomerular filtration rate
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 301 participants (actual)
- Lead sponsor
- AstraZenecaIndustry (pharma, biotech, devices)
- Collaborators
- IQVIA Pty Ltd
- Study start
- 8 Nov 2021 (actual)
- Primary completion
- 10 Feb 2022 (actual)
- Study completion
- 10 Feb 2022 (actual)
- First posted
- 24 Mar 2021 (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 is a non-interventional pilot study with the following objectives:
- Establish scalable methodology for collection of retinal images, blood pressure (BP) and laboratory-based assessments
- Compare the results of a machine-learning algorithm in predicting BP, glycated haemoglobin (HbA1c) and estimated glomerular filtration rate (eGFR) from digital retinal images with clinical and laboratory-based measures
- Determine the required sample size needed to support a future study to fully validate the machine-learning algorithm
Study design
- Observational model
- Case only
- Time perspective
- Prospective
Who may qualify
- Ages
- 35 to 130 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Participants have to be more than 35 years, able to provide written consent and meet the following inclusion criteria: * With or without DM (at least 50% of participants will have an HbA1c ≥ 6.5%* and/or a known diagnosis of DM) * Male or female (at least 40% of participants must be male, and at least 40% must be female)
Key inclusion criteria (4 listed)
- Participant must be ≥ 35 years of age, at the time of signing the informed consent.
- With or without DM (at least 50% of participants will have an HbA1c ≥ 6.5%* and/or a known diagnosis of DM)
- Male or female (at least 40% of participants must be male, and at least 40% must be female)
- Capable of giving signed informed consent as described in Appendix A
Key exclusion criteria (5 listed)
- As judged by the investigator, any evidence of a medical condition which in the investigator's opinion makes it undesirable for the participant to participate in the study for example, but not limited to, if a participant is critically unwell or requiring ongoing emergency treatment
- Any known eye condition that may preclude clear imaging of the retina for example; cataracts
- Involvement in the planning and/or conduct of the study (applies to both AstraZeneca staff and/or staff at the study site).
- Judgment by the investigator that the participant should not participate in the study if the participant is unlikely to comply with study procedures, restrictions and requirements.
- Previous enrolment in the present study with the exception of roll-in participants who may be re-screened and re-enrolled.
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
To assess successful use of methodology for retinal image acquisition, BP (ABPM or manual), HbA1C (laboratory based or point of care test) and e-GFR measurement.
Time frame: up to 66 day
Proportion of participants with completed study procedures and interpretable results including both retinal images, systolic and diastolic BP (ABPM or manual), HbA1c (laboratory based or point of care test) and eGFR at Visit 1
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 4 Jan 2023.
- Derived from this study: PubMed 38618987White T, Selvarajah V, Wolfhagen-Sand F, Svangard N, Mohankumar G, Fenici P, Rough K, Onyango N, Lyons K, Mack C, Nduba V, Noorali Saleh M, Abayo I, Siddiqui A, Majdanska-Strzalka M, Kaszubska K, Hegelund-Myrback T, Esterline R, Manzur A, Parker VER. Prediction of cardiovascular risk factors from retinal fundus photographs: Validation of a deep learning algorithm in a prospective non-interventional study in Kenya. Diabetes Obes Metab. 2024 Jul;26(7):2722-2731. doi: 10.1111/dom.15587. Epub 2024 Apr 15.
- Redacted CSR synopsisLink provided by the sponsor.
- Individual participant dataSharing planned: Yes. Qualified researchers can request access to anonymized individual patient-level data from AstraZeneca group of companies sponsored clinical trials via the request portal. All request will be evaluated as per the AZ disclosure commitment: https://astrazenecagrouptrials.pharmacm.com/ST/Submission/Disclosure.
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. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Prediction of Blood Pressure, Glycated Haemoglobin and Estimated Glomerular Filtration Rate From Digital Retinal Images, run by AstraZeneca at 2 sites in Kenya.
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 4 inclusion and 5 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: finished, as of the sponsor's last update on 4 Jan 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Kenya. Whether a site is taking part right now should be confirmed with that site. See every site.
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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
To assess successful use of methodology for retinal image acquisition, BP (ABPM or manual), HbA1C (laboratory based or point of care test) and e-GFR measurement. (time frame: up to 66 day). 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 NCT04814680, which also lists 1 linked publication.
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 4 Jan 2023.