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Collecting data on health status of people with diabetes and hypertension to develop easy-to-use tests to screen for heart complications.

: A prospective, Cross-Sectional Study to Support Machine Learning Model Development for Screening Cardiovascular Disease Conditions in Populations with Diabetes and Hypertension: Mapping Mobile ECG Device Signals to Gold-Standard Tests - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2025/11/097636
Enrollment
5500
Registered
2025-11-18
Start date
Unknown
Completion date
Unknown
Last updated
2025-12-08

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

Conditions

Health Condition 1: E11- Type 2 diabetes mellitus

Interventions

Intervention1: Nil: Nil Intervention2: Nil: Nil Intervention3: Nil: Nil

Sponsors

Gates Foundation
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Adult patients aged 30 years or above with diabetes and/or hypertension

Exclusion criteria

Exclusion criteria: Currently has a pacemaker implanted Severe comorbid conditions such as cancers, advanced liver or kidney disease, cognitive impairment Pregnant Type 1 Diabetes

Design outcomes

Primary

MeasureTime frame
Based on population studies we anticipate detection of about 10% of the study cohort (approximately 500 subjects) to have cardiovascular disease conditions among those with risk factors of diabetes and/or hypertension to be predicted by the algorithm.Timepoint: This is an observational study and the time point is at the time of recruitment of the participant into the study only. There are no follow up time points.—

Secondary

MeasureTime frame
NilTimepoint: NA—

Countries

India

Contacts

Public ContactSushil Mathew John

Christian Medical College Vellore

rikkisush@cmcvellore.ac.in9443038848

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026