Skip to content

Machine-Learning Algorithm for Prediction of Blood Pressure, Glycated Haemoglobin and Estimated Glomerular Filtration Rate

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

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04814680
Enrollment
301
Registered
2021-03-24
Start date
2021-11-08
Completion date
2022-02-10
Last updated
2023-01-04

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Prediction of Blood Pressure, Glycated Haemoglobin and Estimated Glomerular Filtration Rate From Digital Retinal Images

Keywords

- Machine learning; retinal images; blood pressure; glycated haemoglobin; glomerular filtration rate

Brief 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 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

Interventions

None listed

Sponsors

Iqvia Pty Ltd
CollaboratorINDUSTRY
AstraZeneca
Lead SponsorINDUSTRY

Study design

Observational model
CASE_ONLY
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
35 Years to 130 Years
Healthy volunteers
No

Inclusion criteria

* 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

Exclusion criteria

* 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.

Design outcomes

Primary

MeasureTime frameDescription
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.up to 66 dayProportion 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

Countries

Kenya

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026