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A Novel Method for Involving Women of Color at High Risk for Preterm Birth in Research Priority Setting
Published on: January 12, 2018
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Preterm Birth: Screening and Prediction.
Lyndsay Creswell1, Daniel Lorber Rolnik2, Stephen W Lindow1
1Department of Obstetrics and Gynecology, The Coombe Hospital, Dublin, Ireland.
International Journal of Women'S Health
|December 26, 2023
Summary
Identifying women at high risk of preterm birth (PTB) is crucial. The QUiPP app combines cervical length, fetal fibronectin, and risk factors to improve prediction and management of PTB.
Area of Science:
- Obstetrics and Gynecology
- Maternal-Fetal Medicine
- Neonatal Health
Background:
- Preterm birth (PTB) is a leading cause of neonatal mortality and long-term disability globally.
- Early identification of high-risk pregnancies is essential for timely intervention and improved neonatal outcomes.
- Transvaginal sonographic cervical length (CL) measurement is a key screening tool for PTB.
Purpose of the Study:
- To review the predictive capabilities of current PTB screening methods.
- To evaluate the utility of the QUiPP application in predicting PTB risk.
- To explore emerging research areas for more accurate PTB prediction.
Main Methods:
- Review of existing literature on PTB prediction modalities.
- Assessment of the QUiPP application (v.2) integrating CL, quantitative fetal fibronectin (qfFN), and maternal risk factors.
- Discussion of novel approaches including cervical stiffness, metabolomics, extracellular vesicles, and AI.
Main Results:
- The QUiPP app aids in triaging symptomatic and asymptomatic high-risk women.
- It supports shared decision-making for surveillance, treatment, or reassurance.
- Accurate PTB prediction optimizes antenatal corticosteroid administration.
Conclusions:
- Combining CL, qfFN, and risk factors in the QUiPP app improves PTB risk assessment.
- Emerging technologies show promise for enhancing PTB prediction accuracy.
- Effective PTB prediction is critical for optimizing neonatal care and outcomes.
