High-risk pregnancies according to five risk assessment tools in Northwestern China: Detection and parameters for diagnostic accuracy
<h2>ABSTRACT</h2><h3>Problem considered</h3> High-risk pregnancy can be identified using various risk assessment tools. This study aimed to evaluate the detection and diagnostic accuracy parameters of high-risk pregnancies using five tools. <h3>Methods</h3> A prospective cohort study was conducted in Northwestern China with a sample of 1,211 pregnant women from three tertiary hospitals in Ningxia. Data on demographic characteristics, medical and surgical histories, obstetric and gynecological histories were collected at their first antenatal booking to classify participants into high-risk or non-high-risk groups based on five different risk schemes/tools; they are (i) color coding, (ii) modified Nesbitt, (iii) high-risk scoring standard, (iv) antenatal risk assessment, and (v) Coopland's high-risk pregnancy scoring. Maternal or neonatal mortality and morbidity outcomes were obtained from hospital information systems to serve as the gold standard for comparison. <h3>Results</h3> Among the 1,211 women, 615 (50.8%, 95% CI: 48.0 - 53.6) experienced at least one adverse maternal or neonatal outcome. The detection of high-risk pregnancies ranged from 17.6% to 46.8%. Sensitivity ranged from 23.6% to 52.4%, while specificity varied between 58.1% and 88.6%. All tools demonstrated accuracy levels above 55%, with the color coding tool showing the highest validity. Nearly half of the women experienced maternal or neonatal complications. <h3>Conclusion</h3> These findings highlight the importance of integrating pregnancy risk assessment using the color coding tool into routine antenatal care, alongside laboratory and ultrasound investigations at the first booking, to enhance targeted risk management and improve maternal-fetal outcomes.
Authors
- Bahiyah Abdullah (ORCID: https://orcid.org/0000-0002-6102-8344)
- Yanhua Ning
- Nyi Nyi Naing (ORCID: https://orcid.org/0000-0001-8308-5625)
- Xin Wee Chen (ORCID: https://orcid.org/0000-0002-4785-7189)
- Nadzratulaiman Wan Nordin
- Yang Xiali
Institutions
- Hospital Sungai Buloh (MY)
- Sultan Zainal Abidin University (MY)
Publication Details
- Journal
- Clinical Epidemiology and Global Health
- Published
- 2025-09-25
- DOI
- https://doi.org/10.1016/j.cegh.2025.102191
- Primary Topic
- Demographic Trends and Gender Preferences
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ningxia Medical University