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N/A Completed N=1,232 Randomized Screening

Screening for Pregnancy Related Heart Failure in Nigeria

Cardiomyopathy · Pregnancy Related
Source: ClinicalTrials.gov NCT05438576 ↗
Enrolled (actual)
1,232
Serious AEs
9.1%
Results posted
May 2025
Primary outcomePrimary: Left Ventricular Ejection Fraction (LVEF) <50% — 3; 1; 21; 11 Participants — p=0.032

Summary

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

Outcome Measures

OutcomeResultp-value
PRIMARY
Left Ventricular Ejection Fraction (LVEF) <50%
3; 1; 21; 11 0.032 sig
SECONDARY
Effectiveness of AI-ECG for Cardiomyopathy Detection in the Intervention Arm for Left Ventricular Ejection Fraction (LVEF) ≤ 35%
17; 458; 17; 458
SECONDARY
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 40%
20; 458; 20; 458
SECONDARY
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 45%
22; 457; 22; 457
SECONDARY
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 50%
22; 457; 22; 457

Eligibility Criteria

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
View full record on ClinicalTrials.gov →

Data sourced from ClinicalTrials.gov (NCT05438576). Outcome figures and adverse-event rates are extracted automatically from the registry's posted results and are provided for clinician reference, not as a substitute for the primary publication. Informational only — not medical advice.

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