Abstract
Preeclampsia is a pregnancy-specific disorder defined by new onset of hypertension and proteinuria after 20 weeks of gestation. The early detection of patients at risk of developing preeclampsia is crucial, however, predictive models are still controversial. We aim to evaluate the diagnostic performance of a predictive algorithm in the first trimester of pregnancy, in order to identify patients that will subsequently develop preeclampsia, and to study the effect of aspirin on reducing the rate of this complication in patients classified as high risk by this algorithm. A retrospective cohort including 1132 patients attending prenatal care at Clínica Dávila in Santiago, Chile, was conceived. The risk of developing preeclampsia (early and late onset) was calculated using algorithms previously described by Plasencia et al. Patients classified as high risk, in the first trimester of pregnancy, by these algorithms, were candidates to receive 100 mg/daily aspirin as prophylaxis at the discretion of the attending physician. The overall incidence of preeclampsia in this cohort was 3.5% (40/1132), and the model for early onset preeclampsia prediction detected 33% of patients with early onset preeclampsia. Among the 105 patients considered at high risk of developing preeclampsia, 56 received aspirin and 49 patients did not. Among those who received aspirin, 12% (7/56) developed preeclampsia, which is equal to the rate of preeclampsia (12% (6/49)) of those who did not receive this medication. Therefore, the diagnostic performance of an algorithm combining uterine artery Doppler and maternal factors in the first trimester predicted only one third of patients that developed preeclampsia. Among those considered at high risk for developing the disease using this algorithm, aspirin did not change the incidence of preeclampsia, however, this could be due either to the small study sample size or the type of the study, a retrospective, non-interventional cohort study.
Highlights
The objective of this study was to perform a retrospective cohort study to evaluate the diagnostic performance of a first trimester screening program for PE in a general population setting, using the previously described combined predictive algorithm [57], and to evaluate the effects of aspirin administration in the incidence of PE when patients were classified as high risk using this predictive model
Amongst the high-risk pregnant women whose aspirin administration started before 16 weeks of gestation (n = 53), six cases of PE were observed, whereas six cases were diagnosed between non-aspirin users (n = 49). In this group classified as high-risk, aspirin usage was not associated with a significant reduction in the risk of developing PE (RR: 0,91, 95% confidence interval (CI): 0.23–3.71, p-value = 0.88). This retrospective cohort study shows that in an unselected population, under routine clinical care, the use of a predictive model for PE based on uterine artery pulsatility index and maternal clinical and biophysical risk factors, with a fixed false positive rate of 5%, identified approximately one third of patients that will subsequently develop PE during their pregnancies, including one third of both ePE and late onset PE (loPE)
Farina and colleagues tested this predictive models in a prospective cohort study of 554 pregnancies screened for PE in the first trimester [58]
Summary
Preeclampsia (PE) and gestational hypertensive disorders (GHD) are amongst the most frequent medical conditions affecting pregnancy [1], with an estimated prevalence of approximately 2–10% [2,3,4].These conditions represent one of the leading causes of maternal morbidity and mortality, and approximately 12–14% of maternal deaths occurring worldwide are attributed to these disorder [5,6].PE is associated with a significant increase in perinatal and neonatal morbidity and mortality, mainly due to preterm birth complications, intrauterine growth restriction and fetal death [7].Given its epidemiological and clinical importance, several efforts have been made to predict and prevent the development of PE, using different predictive multiparametric algorithms based on maternal risk factors, uterine artery Doppler pulsatility index, and several plasmatic biomarkers with increasing effectiveness [8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36]. Preeclampsia (PE) and gestational hypertensive disorders (GHD) are amongst the most frequent medical conditions affecting pregnancy [1], with an estimated prevalence of approximately 2–10% [2,3,4]. These conditions represent one of the leading causes of maternal morbidity and mortality, and approximately 12–14% of maternal deaths occurring worldwide are attributed to these disorder [5,6]. Actual predictive models for PE are still controversial and are not currently used in routine clinical care [2,37,38,39,40,41,42,43].
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