Screening for Pregnancy Related Heart Failure in Nigeria

Mayo Clinic

Status: Completed

Conditions: Cardiomyopathy; Pregnancy Related

Treatments: Other: Digital stethoscope electrocardiogram

Study type: Interventional

Funder types: Other; NIH

Identifiers

NCT05438576

22-000539

K12AR084222 (U.S. NIH Grant/Contract)

UL1TR002377 (U.S. NIH Grant/Contract)

Details and patient eligibility

About

This study will evaluate the effectiveness of an artificial intelligence-enabled ECG (AI-ECG) for cardiomyopathy detection in an obstetric population in Nigeria.

Enrollment: 1,232 patients

Sex: Female

Ages: 18 to 49 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Currently pregnant or within 12 months postpartum
• Willing and able to provide informed consent

Exclusion criteria

• Complex congenital heart disease (single ventricle physiology or significant shunts with cardiac structural changes)
• Significant conduction abnormalities (ventricular pacing on recorded ECG, pacemaker dependence, or severely abnormal/bizarre QRS morphology on ECG tracings)
• Unable or unwilling to provide consent

Trial design

Primary purpose: Screening

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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1,232 participants in 2 patient groups

Intervention

Experimental group

Description:

Participants will have ECGs analyzed with artificial intelligence for cardiomyopathy detection.

Treatment:

Other: Digital stethoscope electrocardiogram

Control

No Intervention group

Description:

Participants will have standard clinical ECGs acquired.