- Title
- Do first-trimester screening algorithms for preeclampsia aligned to use of preventative therapies reduce the prevalence of pre-term preeclampsia: A systematic review and meta-analysis
- Creator
- Foster, Ailsa Borbolla; Park, Felicity; Hyett, Jon
- Relation
- Prenatal Diagnosis Vol. 43, Issue 7, p. 950-958
- Publisher Link
- http://dx.doi.org/10.1002/pd.6394
- Publisher
- John Wiley & Sons
- Resource Type
- journal article
- Date
- 2023
- Description
- Objective: Traditional obstetric practice relies upon history-based assessment to screen for preeclampsia and guide preventative therapies but is hampered by low sensitivity, high false-positive rates and low treatment rates. First-trimester screening algorithms represent the most efficacious approach for risk prediction and could target early initiation of aspirin to well-defined high-risk populations. A large randomised controlled trial has demonstrated the clinical benefits of this approach, but widespread practice implementation has remained elusive. Methods: We performed a systematic review and meta-analysis summarising studies linking first-trimester preeclampsia screening algorithms with the initiation of preventative therapy and examined their effect on pre-term preeclampsia rates compared with standard maternity care. Odds ratios were calculated together with 95% confidence intervals. Results: 7 studies with a total of 377,790 participants were included. Within singleton populations, early initiation of aspirin in response to a high-risk screening algorithm result reduced the prevalence of pre-term preeclampsia by 39% compared with routine antenatal care (odds ratio 0.61; 95% CI: 0.52–0.70). There were significant reductions in the prevalence of preeclampsia at <32–34 weeks, preeclampsia at any gestation and stillbirth. Conclusion: First-trimester screening algorithms for preeclampsia aligned with early initiation of preventative therapy with aspirin reduce the prevalence of pre-term preeclampsia.
- Subject
- obstretics; preeclampsia; preventative therapies; systematic review; SDG 3; Sustainable Development Goals
- Identifier
- http://hdl.handle.net/1959.13/1494921
- Identifier
- uon:53922
- Identifier
- ISSN:0197-3851
- Language
- eng
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