Screening For Pregnancy Related Heart Failure In Nigeria

Overview

About this study

The purpose of this studyis to determine the effectiveness of an AI-enabled ECG to detect cardiomyopathy and its impact on clinical outcomes in a predominantly Black obstetric population in Nigeria

Participation eligibility

Participant eligibility includes age, gender, type and stage of disease, and previous treatments or health concerns. Guidelines differ from study to study, and identify who can or cannot participate. There is no guarantee that every individual who qualifies and wants to participate in a trial will be enrolled. Contact the study team to discuss study eligibility and potential participation.

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

Eligibility last updated 7/28/22. Questions regarding updates should be directed to the study team contact.

Participating Mayo Clinic locations

Study statuses change often. Please contact the study team for the most up-to-date information regarding possible participation.

Mayo Clinic Location Status

Rochester, Minn.

Mayo Clinic principal investigator

Demilade Adedinsewo, M.B., Ch.B.

Closed-enrolling by invitation

What is this? (?)
"Close"
Not open to everyone who meets the eligibility criteria, but only those invited to participate by the study team.

Jacksonville, Fla.

Mayo Clinic principal investigator

Demilade Adedinsewo, M.B., Ch.B.

Closed-enrolling by invitation

What is this? (?)
"Close"
Not open to everyone who meets the eligibility criteria, but only those invited to participate by the study team.

More information

Publications

  • Artificial intelligence (AI), and more specifically deep learning, models have demonstrated the potential to augment physician diagnostic capabilities and improve cardiovascular health if incorporated into routine clinical practice. However, many of these tools are yet to be evaluated prospectively in the setting of a rigorous clinical trial-a critical step prior to implementing broadly in routine clinical practice. Read More on PubMed
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CLS-20536239

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