Identification of factors associated with delayed treatment of obstetric hypertensive emergencies
Identification of factors associated with delayed treatment of obstetric hypertensive emergencies
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产科高血压急症延迟治疗相关因素的识别
DOI：
10.1016/j.ajog.2020.02.009
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发表时间：
2020-08-01
影响因子：
9.8
通讯作者：
Heo, Hye J.
中科院分区：
文献类型：
--
作者：
Kantorowska, Agata;Heiselman, Cassandra J.;Heo, Hye J.
BACKGROUND: Obstetric hypertensive emergency is defined as having systolic blood pressure >= 160 mm Hg or diastolic blood pressure >= 110 mm Hg, confirmed 15 minutes apart. The American College of Obstetricians and Gynecologists recommends that acute-onset, severe hypertension be treated with first line-therapy (intravenous labetalol, intravenous hydralazine or oral nifedipine) within 60 minutes to reduce risk of maternal morbidity and death.OBJECTIVE: Our objective was to identify barriers that lead to delayed treatment of obstetric hypertensive emergency.STUDY DESIGN: A retrospective cohort study was performed that compared women who were treated appropriately within 60 minutes vs those with delay in first-line therapy. We identified 604 patients with discharge diagnoses of chronic hypertension, gestational hypertension, or preeclampsia using International Classification of Diseases-10 codes and obstetric antihypertensive usage in a pharmacy database at 1 academic institution from January 2017 through June 2018. Of these, 267 women (44.2%) experienced obstetric hypertensive emergency in the intrapartum period or within 2 days of delivery; the results from 213 women were used for analysis. We evaluated maternal characteristics, presenting symptoms and circumstances, timing of hypertensive emergency, gestational age at presentation, and administered medications. Chi square, Fisher's exact, Wilcoxon rank-sum, and sample t-tests were used to compare the 2 groups. Univariable logistic regression was applied to determine predictors of delayed treatment. Multivariable regression model was also performed; C-statistic and Hosmer and Lemeshow goodness-of-fit test were used to assess the model fit. A result was considered statistically significant at P
