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Cited by 878

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ACOG

·2019·Obstetrics & Gynecology
DOI 10.1097/aog.0000000000003018
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Abstract

Hypertensive disorders of pregnancy constitute one of the leading causes of maternal and perinatal mortality worldwide. It has been estimated that preeclampsia complicates 2-8% of pregnancies globally (). In Latin America and the Caribbean, hypertensive disorders are responsible for almost 26% of maternal deaths, whereas in Africa and Asia they contribute to 9% of deaths. Although maternal mortality is much lower in high-income countries than in developing countries, 16% of maternal deaths can be attributed to hypertensive disorders (). In the United States, the rate of preeclampsia increased by 25% between 1987 and 2004 (). Moreover, in comparison with women giving birth in 1980, those giving birth in 2003 were at 6.7-fold increased risk of severe preeclampsia (). This complication is costly: one study reported that in 2012 in the United States, the estimated cost of preeclampsia within the first 12 months of delivery was $2.18 billion ($1.03 billion for women and $1.15 billion for infants), which was disproportionately borne by premature births (). This Practice Bulletin will provide guidelines for the diagnosis and management of gestational hypertension and preeclampsia.

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Cited by

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Metadata

Venue
Obstetrics & Gynecology
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2019-01
Volume
133
Issue
1
Pages
1-1
ISSN
0029-7844 (ISSN-L)
DOI
10.1097/aog.0000000000003018
OpenAlex
W4233259059
Cited by
878
References
9
FWCI
121.16
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: ACOG. https://app.cochat.ai/papers/10.1097/aog.0000000000003018
The paper
ACOG. (2019). Obstetrics & Gynecology. https://doi.org/10.1097/aog.0000000000003018

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.