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Updated: Jul 7, 2025
A Novel Method for Involving Women of Color at High Risk for Preterm Birth in Research Priority Setting
Published on: January 12, 2018
Preterm Birth: Screening and Prediction
Lyndsay Creswell1, Daniel Lorber Rolnik2, Stephen W Lindow1
1Department of Obstetrics and Gynecology, The Coombe Hospital, Dublin, Ireland.
Insights
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.
Abstract:
Preterm birth (PTB) affects approximately 10% of births globally each year and is the most significant direct cause of neonatal death and of long-term disability worldwide. Early identification of women at high risk of PTB is important, given the availability of evidence-based, effective screening modalities, which facilitate decision-making on preventative strategies, particularly transvaginal sonographic cervical length (CL) measurement. There is growing evidence that combining CL with quantitative fetal fibronectin (qfFN) and maternal risk factors in the extensively peer-reviewed and validated QUanititative Innovation in Predicting Preterm birth (QUiPP) application can aid both the triage of patients who present as emergencies with symptoms of preterm labor and high-risk asymptomatic women attending PTB surveillance clinics. The QUiPP app risk of delivery thus supports shared decision-making with patients on the need for increased outpatient surveillance, in-patient treatment for preterm labor or simply reassurance for those unlikely to deliver preterm. Effective triage of patients at preterm gestations is an obstetric clinical priority as correctly timed administration of antenatal corticosteroids will maximise their neonatal benefits. This review explores the predictive capacity of existing predictive tests for PTB in both singleton and multiple pregnancies, including the QUiPP app v.2. and discusses promising new research areas, which aim to predict PTB through cervical stiffness and elastography measurements, metabolomics, extracellular vesicles and artificial intelligence.
