Introduction: Hypertensive disorders of pregnancy have been the most frequent cause of maternal death in Norway since 1996 and are strongly associated with substandard care. In the UK, the number of maternal deaths due to hypertensive disorders has decreased drastically due to the implementation of updated guidelines, indicating a potential for reducing the number of deaths in other countries as well. Through audits of maternal deaths, we aim to prevent future deaths from hypertensive disorders in pregnancy by identifying suboptimal factors in treatment.
Material And Methods: Maternal deaths in Norway from 1996 to 2014 were identified through linked registries. The Norwegian Maternal Mortality Audit Group performed all case assessments included in this study, classified the cause of death, evaluated the treatment, and identified suboptimal factors to care in each case. Emphasis was placed on antihypertensive treatment, timing of delivery, stabilization before delivery, and quality of care. Learning points were prepared to improve the treatment of hypertensive disorders of pregnancy.
Results: We identified 74 maternal deaths. The maternal mortality rate was 6.5 deaths per 100 000 live births. The most common cause of death was hypertensive disorders (n = 16 deaths). In 14 of these deaths (87%), the audit group concluded that improvements to care could have made a difference to the outcome.
Conclusions: In 1996-2014, hypertensive disorders were the most common cause of maternal death in Norway. Our study indicates that such deaths can be prevented by improvements in antihypertensive treatment and the timing of delivery.
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http://dx.doi.org/10.1111/aogs.13357 | DOI Listing |
JAMA Cardiol
January 2025
National Heart and Lung Institute, Imperial College London, United Kingdom.
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View Article and Find Full Text PDFActa Gastroenterol Belg
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View Article and Find Full Text PDFArterioscler Thromb Vasc Biol
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Department of Applied Mathematics, Department of Biology, Cheriton School of Computer Science, and School of Pharmacology, University of Waterloo, ON, Canada.
Preeclampsia is a multisystem hypertensive disorder that manifests itself after 20 weeks of pregnancy, along with proteinuria. The pathophysiology of preeclampsia is incompletely understood. Artificial intelligence, especially machine learning with its capability to identify patterns in complex data, has the potential to revolutionize preeclampsia research.
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Methods: This was a cross-sectional, real-life study.
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