Details

Autor(en) / Beteiligte

• Bartsch, Emily
• Medcalf, Karyn E
• Park, Alison L
• Ray, Joel G

Titel

Clinical risk factors for pre-eclampsia determined in early pregnancy: systematic review and meta-analysis of large cohort studies

Ist Teil von

• BMJ (Online), 2016-04, Vol.353, p.i1753

Ort / Verlag

England

Erscheinungsjahr

2016

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• To develop a practical evidence based list of clinical risk factors that can be assessed by a clinician at ≤ 16 weeks' gestation to estimate a woman's risk of pre-eclampsia. Systematic review and meta-analysis of cohort studies. PubMed and Embase databases, 2000-15. Cohort studies with ≥ 1000 participants that evaluated the risk of pre-eclampsia in relation to a common and generally accepted clinical risk factor assessed at ≤ 16 weeks' gestation. Two independent reviewers extracted data from included studies. A pooled event rate and pooled relative risk for pre-eclampsia were calculated for each of 14 risk factors. There were 25,356,688 pregnancies among 92 studies. The pooled relative risk for each risk factor significantly exceeded 1.0, except for prior intrauterine growth restriction. Women with antiphospholipid antibody syndrome had the highest pooled rate of pre-eclampsia (17.3%, 95% confidence interval 6.8% to 31.4%). Those with prior pre-eclampsia had the greatest pooled relative risk (8.4, 7.1 to 9.9). Chronic hypertension ranked second, both in terms of its pooled rate (16.0%, 12.6% to 19.7%) and pooled relative risk (5.1, 4.0 to 6.5) of pre-eclampsia. Pregestational diabetes (pooled rate 11.0%, 8.4% to 13.8%; pooled relative risk 3.7, 3.1 to 4.3), prepregnancy body mass index (BMI) >30 (7.1%, 6.1% to 8.2%; 2.8, 2.6 to 3.1), and use of assisted reproductive technology (6.2%, 4.7% to 7.9%; 1.8, 1.6 to 2.1) were other prominent risk factors. There are several practical clinical risk factors that, either alone or in combination, might identify women in early pregnancy who are at "high risk" of pre-eclampsia. These data can inform the generation of a clinical prediction model for pre-eclampsia and the use of aspirin prophylaxis in pregnancy.