Formative research to optimize pre-eclampsia risk-screening and prevention (PEARLS): study protocol

  • on behalf of the PEARLS Trial collaborative group

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Background: Pre-eclampsia is a leading cause of maternal and neonatal mortality, affecting nearly 5% of pregnant women worldwide. Accurate and timely risk-screening of pregnant women is essential to start preventive therapies as early as possible, including low-dose aspirin and calcium supplementation. In the formative phase for the “Preventing pre-eclampsia: Evaluating AspiRin Low-dose regimens following risk Screening” (PEARLS) trial, we aim to validate and implement a pre-eclampsia risk-screening algorithm, and validate an artificial intelligence (AI) ultrasound for gestational age estimation. In the trial phase, we will compare different daily aspirin doses (75 mg v 150 mg) for pre-eclampsia prevention and postpartum bleeding. This study protocol outlines the mixed-methods formative phase of PEARLS, which will identify challenges and the feasibility of implementing these activities in participating facilities in Ghana, Kenya, and South Africa. Methods: We will employ qualitative and quantitative methods to identify factors that may influence trial implementation. In-depth interviews and focus group discussions with policy stakeholders, research midwives, health workers, and pregnant women will explore the barriers, facilitators, and acceptability of pre-eclampsia risk screening, AI ultrasound, and aspirin uptake. A cross-sectional survey of antenatal care and maternity health workers will assess current clinical practices around pre-eclampsia and willingness to participate in the trial activities. Data will be analyzed using thematic analysis and triangulated across sources and participant groups. The findings will inform trial design and help optimize implementation. Discussion: The research will provide critical insights into the feasibility of pre-eclampsia risk screening and AI ultrasound for gestational age estimation in resource-limited settings. By identifying factors that can influence implementation of pre-eclampsia prevention and care pathways, the findings will inform successful execution of the PEARLS trial, and post-research scale-up activities. This, in turn, can help reduce the prevalence of pre-eclampsia, and improve maternal and newborn outcomes in high-burden settings. Trial registration: PACTR202403785563823 || pactr.samrc.ac.za (Date of registration: 12 March 2024).

Original languageEnglish
Article number44
JournalReproductive Health
Volume22
Issue number1
DOIs
Publication statusPublished - Dec 2025

Keywords

  • Antenatal care
  • Artificial Intelligence Ultrasound
  • Aspirin prophylaxis
  • Gestational age estimation
  • Hypertensive disorders of pregnancy
  • LMICs
  • Maternal health
  • Mixed-methods
  • Pre-eclampsia
  • Protocol
  • Risk screening

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