Secondary Logo

Journal Logo

Screening and Prevention of Preeclampsia

Poon, Liona C.*; Sahota, Daljit

Section Editor(s): Li, Yan-Li; Pan, Yang

doi: 10.1097/FM9.0000000000000005
Review
Open

Preeclampsia (PE) is a multisystem disorder of pregnancy classically characterized by hypertension with significant proteinuria after 20 weeks’ gestation. This disorder is one of the leading causes of maternal and perinatal morbidity and mortality. PE can be subdivided into preterm PE (with delivery at <37 weeks’ gestation) and term PE (with delivery at ≥37 weeks’ gestation). Preterm PE is associated with a higher risk of adverse maternal and perinatal outcomes than term PE. Traditional method of screening as recommended by professional guidelines has limited predictive performance and therefore should be updated to reflect recent scientific evidence that the target of screening should be preterm PE, the best way to identify the high-risk group is the Bayes-based method that combines maternal risk factors and biomarkers, the threshold should be set at screen positive rate of 10%, aspirin should be started before 16 weeks’ gestation, and the daily dose should be higher than 100 mg.

Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Shatin, Hong Kong 999077, China.

Corresponding author: Prof. Liona C. Poon, The Chinese University of Hong Kong, Hong Kong 999077, China. E-mail: liona.poon@cuhk.edu.hk

Received April 23, 2019

This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0

Back to Top | Article Outline

Introduction

Preeclampsia (PE) is a multisystem disorder of pregnancy classically characterized by hypertension with significant proteinuria after 20 weeks’ gestation.1–7 This disorder affects 2%–5% of pregnant women and is one of the leading causes of maternal and perinatal morbidity and mortality. Worldwide, 76,000 women and 500,000 babies die yearly from this disorder.8 PE can be subdivided into preterm PE (with delivery at <37 weeks’ gestation) and term PE (with delivery at ≥37 weeks’ gestation). Preterm PE is associated with a higher risk of adverse maternal and perinatal outcomes than late-onset or term PE.9,10

The desire to predict PE effectively in the first trimester of pregnancy is driven by the need to identify pregnant women who are at high risk of developing the disorder, so that preventive measures can be initiated as early as possible in order to improve placentation and reduce the incidence as well as severity of the disorder.11,12 Despite the complex pathophysiology of PE, recent advances have made it possible to predict and prevent preterm PE in the first trimester of pregnancy.

Back to Top | Article Outline

First trimester screening for preterm preeclampsia

The traditional approach for the identification of high-risk women for PE follows the recommendations of professional organizations, such as National Institute for Health and Care Excellence (NICE) 13 and American College of Obstetricians and Gynecologists (ACOG).14–16 Risk factors include hypertensive disease in previous pregnancy, chronic hypertension, chronic renal disease, diabetes mellitus, autoimmune disease, nulliparity, advanced maternal age, obesity, family history of PE, and prolonged interpregnancy interval.13–16 This checklist-based approach essentially treats each risk factor as a separate screening test with additive detection rate (DR) and screen positive rate (SPR). Furthermore, evidence supporting these recommendations is mainly based on retrospective epidemiological studies on evaluating the relationship between individual risk factor and the development of PE; and most studies have not differentiated between preterm and term PE.

A large systematic review and meta-analysis of 92 studies, including 25,356,688 pregnancies, have determined the association between clinical risk factors identified before 16 weeks’ gestations and the risk of PE.17 Women with prior history of PE and chronic hypertension are the most significant risk factors and have relative risks (RR) of 8.4 (95% CI: 7.1–9.9) and 5.1 (95% CI: 4.0–6.5) for PE, respectively. Other clinical risk factors for PE include nulliparity (RR: 2.1; 95% CI: 1.9–2.4), maternal age >35 years (RR: 1.2; 95% CI: 1.1–1.3), chronic kidney disease (RR: 1.8; 95% CI: 1.5–2.1), conception by assisted reproductive technology (RR: 1.8; 95% CI: 1.6–2.1), prepregnancy body mass index (BMI) of >30 kg/m2 (RR: 2.8; 95% CI: 2.6–3.1), and preexisting diabetes mellitus (RR: 3.7; 95% CI: 3.1–4.3).17

An alternative approach to screening for PE, which allows estimation of individual patient-specific risks of PE with delivery before a specified gestation, is to use Bayes theorem to combine the a priori risk from maternal characteristics, medical and obstetric history with the results of various combinations of biophysical and biochemical measurements. Extensive research in the last decade has led to the identification of four potentially useful biomarkers at 11–13 weeks’ gestation: mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI), serum pregnancy-associated plasma protein-A (PAPP-A), and serum placental growth factor (PlGF).

It has been well documented that women who are destined to develop PE have an elevated blood pressure (BP) in the first trimester of pregnancy.18–21 The measurements of BP should be undertaken using a standardized protocol; briefly, the BP is measured in both arms simultaneously using validated automated devices with correct positioning of women and the average of the four calculated MAP measurements is used for risk assessment.22 Abnormal uteroplacental circulation could be observed as abnormal Doppler in the uterine arteries by ultrasound (increased UtA-PI) from as early as the first trimester of pregnancy. In order to achieve reproducible, consistent, and accurate screening performance, standardization for the measurement of UtA-PI is required. Transabdominal ultrasound is used to obtain a sagittal section of the uterus and to locate the internal cervical os; then, ultrasound transducer is tilted to the lateral sides of the cervix, the uterine arteries are identified with the use of color Doppler flow mapping at the level of the internal cervical os. Pulsed wave Doppler is then performed with the sampling gate set at 2 mm to cover the vessel. The UtA-PI and peak systolic velocity are measured automatically by the ultrasound machine when three similar consecutive waveforms are obtained. The peak systolic velocity must be >60 cm/s to ensure measurement of the UtA-PI is performed at the level of the internal os.23 The average of the left and right UtA-PI is used for risk assessment. Maternal serum PAPP-A and PlGF have been investigated extensively, and have shown promising results in the early prediction of PE when values are observed to be reduced. These placental proteins have been implicated in the normal development of the placenta. Both PAPP-A and PlGF can be measured by several commercially available platforms of automated analyzers that provide reproducible results within 20–40 minutes of sampling. Certain maternal and pregnancy characteristics affect the crude values of these biomarkers and it is therefore necessary to express the measured values as multiple of medians, adjusting for these characteristics. It is also necessary to adjust for analyzer and reagents used for biochemical markers.24–26

The algorithm of a combination of maternal risk factors, MAP, UtA-PI, PAPP-A, and PlGF, was developed from a study of 35,948 singleton pregnancies, including 1058 pregnancies (2.9%) that experienced PE; the DR of preterm PE and term PE were 75% and 47%, respectively, at false positive rate (FPR) of 10%.27 Subsequently, data from three reported prospective nonintervention screening studies at 11–13 weeks’ gestation in a combined total of 61,174 singleton pregnancies, including 1770 (2.9%) that developed PE, have demonstrated that screening by a combination of maternal risk factors, MAP, UtA-PI, and PlGF and using a risk cutoff of 1 in 100 for preterm PE in Caucasian women, the SPR was 10% and DR for preterm and term PE were 69% and 40%, respectively. With the same method of screening and risk cutoff in women of Afro-Caribbean racial origin, the SPR was 34% and DR for preterm and term PE were 92% and 75%, respectively.26

In the latest National Institute for Health Research (UK) commissioned prospective validation study of the Bayes-based model in 16,747 pregnancies, including 473 (2.8%) women that developed PE, the SPR by the NICE method was 10.3% and the DR for all PE was 30% and for preterm PE it was 41%. The DR of the mini-combined test (maternal factors, MAP, and PAPP-A) for all PE was 43%, which was superior to that of the NICE method by 12.1% (95% CI: 7.9%–16.2%). In screening for preterm PE by a combination of maternal factors, MAP, UtA-PI, and PlGF, the DR was 82%, which was higher than that of the NICE method by 41.6% (95% CI:33.2%–49.9%).28 The addition of PAPP-A to this combined model did not improve the overall screening performance.

A secondary analysis of data from the ASPRE (Aspirin for Evidence-Based Preeclampsia Prevention) trial of a total of 34,573 women with singleton pregnancies who underwent prospective screening for preterm PE, including 239 (0.7%) cases of preterm PE, showed that in ACOG or NICE screen positive women who were screen negative by the Bayes-based method, the risk of preterm PE was reduced to within or below background levels.29 The study demonstrated that at least one of the ACOG criteria was fulfilled in 22,287 (64.5%) pregnancies and the incidence of preterm PE was 0.97% (95% CI: 0.85%–1.11%); in the subgroup that was Bayes method screen positive, the incidence was 4.8% (95% CI: 4.14%–5.55%), in those who were screen negative, it was 0.25% (95% CI: 0.18%-0.33%) and the relative incidence in Bayes method negative to Bayes method positive, the incidence was 5.1% (95% CI: 3.7%–7.1%). In 1392 (4%) pregnancies, at least one of the NICE high-risk criteria was fulfilled and in this group the incidence of preterm PE was 5.17% (95% CI: 4.13%–6.46%); in the subgroups of screen positive and screen negative by the Bayes method, the incidence of preterm PE was 8.71% (95% CI: 6.93%–10.89%) and 0.65% (95% CI: 0.25%–1.67%), respectively, and the relative incidence was 7.5% (95% CI: 2.8%–20.5%). In 2360 (6.8%) pregnancies with at least two of the NICE moderate-risk criteria, the incidence of preterm PE was 1.74% (95% CI: 1.28%–2.35%); in the subgroups of screen positive and screen negative by the Bayes method, the incidence was 4.91% (95% CI: 3.54%–6.79%) and 0.42% (95% CI: 0.2%–0.86%), respectively, and the relative incidence was 8.5% (95% CI:3.8%–19.2%).29 These results provide further evidence to support risk-based screening using biomarkers.

Previous studies have demonstrated that biomarker values derived from Chinese populations are different from those derived from non-Chinese populations.30–33 These variations or changes in biomarkers can affect the screening performance. A case-control study including 3000 normotensive and 30 preeclamptic pregnant women evaluated the first-trimester PE prediction test in a South Chinese population.30 Biomarker values were adjusted for maternal and pregnancy characteristics with the use of published expected values based on European data.31 The study demonstrated that the predictive performance based on European algorithms in the South Chinese population was lower than those obtained from the original studies. The investigators postulated that the poor performance of screening was due to the lower rate of PE in the South Chinese population and the under-measurement of MAP and UtA-PI.30 An Asia-wide prospective validation study of the Bayes-based model is underway and results are expected in mid-2019 (ClinicalTrials.gov Identifier: NCT03554681).

Back to Top | Article Outline

Prevention of preeclampsia

Evidence from the aforementioned studies indicates that there is an effective screening tool for the identification of women at risk of developing preterm PE. This allows early introduction of prophylactic treatment and therapeutic intervention. Several approaches have been proposed to prevent PE, including the administration of low-dose aspirin, heparin, antioxidants, calcium supplementation, proton pump inhibitor, or metformin. The only proven effective preventive strategy is the administration of low-dose aspirin to high-risk women for preterm PE at <16 weeks’ gestation.33–50

In 1978, Goodlin et al. described a patient with recurrent PE and thrombocytopenia who seemed to have benefited from aspirin prophylaxis.37 Crandon and Isherwood demonstrated that nulliparous pregnant women who had taken aspirin or aspirin-containing compounds for more than once a fortnight throughout pregnancy had a lower risk of PE than those who had no reported history of aspirin consumption.51 In 1985, a randomized, open-labeled trial showed that women at risk for PE or fetal growth restriction (FGR), based on obstetric history, who received 300 mg of dipyridamole and 150 mg of aspirin since 12 weeks of gestation until delivery, were not complicated by PE, fetal loss, or severe FGR, compared to those in the nonintervention group.52

A landmark individual patient data meta-analysis, including 31 randomized trials of PE prevention (n = 32,217 women), showed that patients who received antiplatelet agents especially aspirin, for the prevention of PE, had a 10% reduction in the rate of PE (RR: 0.90; 95% CI: 0.84–0.97), irrespective of aspirin dosage, starting time, and indications.53 Bujold et al. demonstrated that low-dose aspirin started at 16 weeks or earlier in patients at risk of PE had a substantial reduction in the rate of PE (RR: 0.47; 95% CI: 0.34–0.65). However, aspirin started after 16 weeks of gestation did not decrease the rate of PE (RR: 0.81; 95% CI: 0.87–1.10).54

There is now substantial evidence from the ASPRE trial that the rate of preterm PE can be reduced by >60% by low-dose aspirin started at 11–14 weeks of gestation in high-risk women identified by the Bayes-based prediction model.35 In this multicenter, double-blind, placebo-controlled trial, 1776 women with singleton pregnancies at high risk of preterm PE were randomly assigned to receive aspirin, at a dose of 150 mg per night, or placebo from 11 to 14 weeks of gestation until 36 weeks.35 The primary outcome was delivery with PE before 37 weeks of gestation (preterm PE). Preterm PE occurred in 13 (1.6%) participants in the aspirin group and in 35 (4.3%) in the placebo group (odds ratio [OR] in the aspirin group 0.38; 95% CI: 0.20–0.74; P = 0.004). Adherence was good with a reported intake of 85% or more of the required number of tablets in 80% of the participants.35 There were no significant between-group differences in adverse events and serious adverse events, concluding that low-dose aspirin was considered safe.35 Furthermore, a secondary analysis of data of 1620 participants with 1571 live-born neonates showed that the total length of stay in neonatal intensive care (NICU) was substantially longer in the placebo group than in the aspirin group (1696 vs. 531 days). This was a reflection of significantly shorter mean lengths of stay in babies admitted to the NICU in the aspirin group compared to the placebo group (11.1 vs. 31.4 days; a reduction of 20.3 days).55 Overall, in the whole trial population, including zero lengths of stay for those who were not admitted to the NICU, the mean length of stay was longer in the placebo group than in the aspirin group (2.06 vs. 0.66 days; reduction of 1.4 days). This corresponded to a reduction in length of stay of 68%.55

The latest systematic review and meta-analysis, including 16 randomized controlled trials with a total of 18,907 participants, has demonstrated that the administration of aspirin is associated with a reduction in the rate of preterm PE (RR: 0.62; 95% CI: 0.45–0.87).36 However, there is no significant effect on term PE (RR: 0.92; 95% CI: 0.70–1.21). Only the subgroup in which aspirin is started at ≤16 weeks of gestation at a dose of ≥100 mg/day is associated with a reduction in the frequency of preterm PE (RR: 0.33; 95% CI: 0.19–0.57, P = 0.0001). Either the initiation of aspirin at >16 weeks or the daily dose of <100 mg is not associated with a reduction in preterm or term PE.36

Back to Top | Article Outline

Benefit and harm

The ASPRE approach that screens for preterm PE followed by a simple intervention of daily aspirin can be assessed in terms of “benefits” and “harms.” Benefits and harms are simple concepts, readily understood by most individuals and frequently applied to medicine and health care, as every intervention, no matter how innocuous it may appear, carries both benefits and harms. Any prediction and intervention study has to balance the benefits and harms in the context of the condition being screened for and the impact, if any, of the treatment intervention being offered in order to practice “good” evidence-based medicine. Ideally, a screening and treatment protocol should offer all the benefits and none of the harms; the reality, however, is that there is always some compromise.

Screening benefits would be early awareness, by both the physicians and patients, that the pregnancy is at increased risk of developing preterm PE, clinical interventions to increase pregnancy duration by preventing or delaying PE, thus reducing NICU admission duration, and ultimately preventing reduction in maternal life expectancy as well as future risk of cardiovascular disease.55–57 Women with a history of PE, relative to those without, have a twofold increased risk of major coronary events, with risks being even higher if the pregnancy was also complicated by FGR (threefold) or preterm delivery (fivefold). Screening and treatment harms would include unnecessary induced anxiety and potential indirect side effects associated with aspirin and overtreatment. A recent registry analysis of Danish and Norwegian mother–child pairs has reported that children exposed to aspirin and paracetamol during pregnancy have an elevated risk of cerebral palsy.58 However, this Scandinavian-based retrospective registry has major limitations. First, the aspirin dosage effect has not been assessed. Second, whether cerebral palsy is a result of the delivery process or other potential antenatal event has not been evaluated. A meta-analysis review on behalf of the US Preventive Services Task Force in 2015 concluded that daily aspirin at dosages of up to 160 mg per day was not associated with an increased risk of maternal postpartum hemorrhage (RR: 1.02; 95% CI: 0.96–1.09) and perinatal mortality (RR: 0.92; 95% CI: 0.76–1.11), but was associated with a risk reduction in preterm birth (RR: 0.86; 95% CI: 0.76–0.98), FGR (RR: 0.80; 95% CI: 0.65–0.99), and PE (RR: 0.76; 95% CI: 0.62–0.95).59

Cost-benefit or cost-utility decision analysis modeling is frequently used to determine both the optimum strategy and incremental cost of one strategy over another to decide whether a new strategy or approach is an improvement over alternatives. The impact or potential benefits versus that of potential harms, provided they can be represented either monetarily or by their impact on quality of life, is reported. This approach has been used to assess the cost-effectiveness of Down syndrome screening and more recently has been reported for first-trimester PE screening and treatment.60,61

An alternative and increasingly adopted approach is to perform decision analysis based on assessment of net benefit relative to harm as “exchange rates”/“threshold probabilities” (pt) between potential strategies change.62,63 Decision curve analysis (DCA) has an advantage over traditional diagnostic/screening performance assessment because DCA assesses clinical utility, whereas the latter are measures of diagnostic/screening accuracy. A clinical judgment of the relative value of benefits (treating a true positive [TP] case) and harms (treating a false positive [FP] case) associated with screening prediction models can then be assessed on a common scale. To compare strategies at a given threshold probability, the net benefit (for the screening) can be determined as (TP − FP (pt/(1 − pt))/n), where n is the number of cases screened and pt is the threshold probability at which an individual is screened “high risk” as opposed to “low risk.” The DCA could, therefore, be used to assess the potential benefit/harm of preterm PE prediction performance within the ASPRE trial. After correcting for the effect of aspirin use in those randomized to aspirin, it was estimated that the DR of the first-trimester screening was 77% for preterm PE, at 10% FPR, using a risk cutoff of 1%,35,64 a figure consistent with the 75% DR reported in an earlier nonintervention study.29

For a threshold of 1% (1:99), the Bayes-based screening model using maternal risk factors in combination with biomarkers correctly predicted 138 of the 180 women who developed preterm PE and identified 2375 of the 25,167 unaffected women as FPs. The net benefit is therefore (138–2375 × (1/99))/25,347 = 0.45%. The net benefit of “no screen” and offering all aspirin would be (180–25,167 × (1/99))/25,347 = −0.29%, an absolute difference of 0.74%. Offering no screening and prescribing aspirin would be considered harmful. Overall, offering screening implies that for every 1000 patients screened, ≈8 true positives are identified without increasing FPR. The net benefit however will change. Had ASPRE used a lower threshold and adopted a FPR of 30%, a threshold probability would be 0.27% (1:370), assuming that TP rate of the screening test increased to 90% and then net benefit of screening increases to 0.58% ((162–7550 × 0.2/99.8)/25,347), whereas no screening would be 0.51% ((180–25,167 × 0.2/99.8)/25,347) and thus still beneficial, although it would detect only ≈1 additional TP case.

Back to Top | Article Outline

Conclusion

Traditional method of screening as recommended by professional guidelines has limited predictive performance and therefore should be updated to reflect recent scientific evidence that the target of screening should be preterm PE, the best way to identify the high-risk group is the Bayes-based method that combines maternal risk factors and biomarkers, the threshold should be set at SPR of 10%, aspirin should be started before 16 weeks’ gestation, and the daily dose should be higher than 100 mg.

Back to Top | Article Outline

Funding

None.

Back to Top | Article Outline

Conflicts of Interest

Liona C. Poon has received speaker fees and consultancy payments from Roche Diagnostics. In addition, she has received in-kind contributions from Roche Diagnostics, PerkinElmer, Thermo Fisher Scientific and GE Healthcare.

Back to Top | Article Outline

References

[1]. Redman CW, Sargent IL. Latest advances in understanding preeclampsia. Science 2005;308(5728):15924. doi: 10.1126/science.1111726.
[2]. Roberts JM, Gammill HS. Preeclampsia: recent insights. Hypertension 2005;46(6):1243–1249. doi: 10.1161/01.HYP.0000188408.49896.c5.
[3]. Sibai B, Dekker G, Kupferminc M. Pre-eclampsia. Lancet 2005;365(9461):785–799. doi: 10.1016/S0140-6736(05)17987-2.
[4]. Duley L. The global impact of pre-eclampsia and eclampsia. Semin Perinatol 2009;33(3):130–137. doi: 10.1053/j.semperi.2009.02.010.
[5]. Lindheimer MD, Roberts JM, Cunningham GC. Lindheimer MD, Roberts JM, Cunningham GC, et al The clinical spectrum of preeclampsia. Chesley's Hypertensive Disorders in Pregnancy, San Diego: Elsevier; 2009,25-36.
[6]. Steegers EA, von Dadelszen P, Duvekot JJ, et al Pre-eclampsia. Lancet 2010;376(9741):631–644. doi: 10.1016/S0140-6736(10)60279-6.
[7]. Mol BWJ, Roberts CT, Thangaratinam S, et al Pre-eclampsia. Lancet 2016;387(10022):999–1011. doi: 10.1016/S0140-6736(15)00070-7.
[8]. Kuklina EV, Ayala C, Callaghan WM. Hypertensive disorders and severe obstetric morbidity in the United States. Obstet Gynecol 2009;113(6):1299–1306. doi: 10.1097/AOG.0b013e3181a45b25.
[9]. Lisonkova S, Joseph KS. Incidence of preeclampsia: risk factors and outcomes associated with early- versus late-onset disease. Am J Obstet Gynecol 2013;209(6):544.e1–544.e12. doi: 10.1016/j.ajog.2013.08.019.
[10]. Lisonkova S, Sabr Y, Mayer C, et al Maternal morbidity associated with early-onset and late-onset preeclampsia. Obstet Gynecol 2014;124(4):771–781. doi: 10.1097/AOG.0000000000000472.
[11]. Poon LC, Nicolaides KH. Early prediction of preeclampsia. Obstet Gynecol Int 2014;2014:297397. doi: 10.1155/2014/297397.
[12]. Poon LC, David McIntyre H, Hyett JA, et al The first-trimester of pregnancy: a window of opportunity for prediction and prevention of pregnancy complications and future life. Diabetes Res Clin Pract 2018;145:20–30. doi: 10.1016/j.diabres.2018.05.002.
[13]. National Collaborating Centre for Women's and Children's Health (UK). Hypertension in Pregnancy: The Management of Hypertensive Disorders During Pregnancy. London: RCOG Press; 2010.
[14]. American College of Obstetricians and Gynecologists. Task Force on Hypertension in Pregnancy. Hypertension in Pregnancy. 2013. Available at: https://www.acog.org/∼/media/Task%20Force%20and%20Work%20Group%20Reports/public/HypertensioninPregnancy.pdf.
[15]. LeFevre ML, Force USPST. Low-dose aspirin use for the prevention of morbidity and mortality from preeclampsia: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med 2014;161(11):819–826. doi: 10.7326/m14-1884.
[16]. ACOG Committee Opinion No. 743: low-dose aspirin use during pregnancy. Obstet Gynecol 2018;132(1):e44–e52. doi: 10.1097/AOG.0000000000002709.
[17]. Bartsch E, Medcalf KE, Park AL, et al Clinical risk factors for pre-eclampsia determined in early pregnancy: systematic review and meta-analysis of large cohort studies. BMJ 2016;353:i1753. doi: 10.1136/bmj.i1753.
[18]. Moutquin JM, Rainville C, Giroux L, et al A prospective study of blood pressure in pregnancy: prediction of preeclampsia. Am J Obstet Gynecol 1985;151(2):191–196. doi: 10.1016/0002-9378(85)90010-9.
[19]. Higgins JR, Walshe JJ, Halligan A, et al Can 24-hour ambulatory blood pressure measurement predict the development of hypertension in primigravidae? Br J Obstet Gynaecol 1997;104(3):356–362. doi: 10.1111/j.1471-0528.1997.tb11468.x.
[20]. Poon LC, Kametas NA, Pandeva I, et al Mean arterial pressure at 11(+0) to 13(+6) weeks in the prediction of preeclampsia. Hypertension 2008;51(4):1027–1033. doi: 10.1161/HYPERTENSIONAHA.107.104646.
[21]. Poon LC, Kametas NA, Valencia C, et al Hypertensive disorders in pregnancy: screening by systolic diastolic and mean arterial pressure at 11–13 weeks. Hypertens Pregnancy 2011;30(1):93–107. doi: 10.3109/10641955.2010.
[22]. Poon LC, Zymeri NA, Zamprakou A, et al Protocol for measurement of mean arterial pressure at 11–13 weeks’ gestation. Fetal Diagn Ther 2012;31(1):42–48. doi: 10.1159/000335366.
[23]. Khalil A, Nicolaides KH. How to record uterine artery Doppler in the first trimester. Ultrasound Obstet Gynecol 2013;42(4):478–479. doi: 10.1002/uog.12366.
[24]. Wright A, Wright D, Ispas CA, et al Mean arterial pressure in the three trimesters of pregnancy: effects of maternal characteristics and medical history. Ultrasound Obstet Gynecol 2015;45(6):698–706. doi: 10.1002/uog.14783.
[25]. Tayyar A, Guerra L, Wright A, et al Uterine artery pulsatility index in the three trimesters of pregnancy: effects of maternal characteristics and medical history. Ultrasound Obstet Gynecol 2015;45(6):689–697. doi: 10.1002/uog.14789.
[26]. Tan MY, Syngelaki A, Poon LC, et al Screening for pre-eclampsia by maternal factors and biomarkers at 11–13 weeks’ gestation. Ultrasound Obstet Gynecol 2018;52(2):186–195. doi: 10.1002/uog.19112.
[27]. O’Gorman N, Wright D, Syngelaki A, et al Competing risks model in screening for preeclampsia by maternal factors and biomarkers at 11–13 weeks gestation. Am J Obstet Gynecol 2016;214:103.e1–103.e12. doi: 10.1016/j.ajog.2015.08.034.
[28]. Tan MY, Wright D, Syngelaki A, et al Comparison of diagnostic accuracy of early screening for pre-eclampsia by NICE guidelines and a method combining maternal factors and biomarkers: results of SPREE. Ultrasound Obstet Gynecol 2018;51:743–750. doi: 10.1002/uog.19039.
[29]. Poon LC, Rolnik DL, Tan MY, et al ASPRE trial: incidence of preterm pre-eclampsia in patients fulfilling ACOG and NICE criteria according to risk by FMF algorithm. Ultrasound Obstet Gynecol 2018;51:738–742. doi: 10.1002/uog.19019.
[30]. Cheng Y, Leung TY, Law LW, et al First trimester screening for pre-eclampsia in Chinese pregnancies: case-control study. BJOG 2018;125(4):442–449. doi: 10.1111/1471-0528.14970.
[31]. Leung TY, Spencer K, Leung TN, et al Higher median levels of free beta-hCG and PAPP-A in the first trimester of pregnancy in a Chinese ethnic group. Implication for first trimester combined screening for Down's syndrome in the Chinese population. Fetal Diagn Ther 2006;21(1):140–143. doi: 10.1159/000089064.
[32]. Liao C, Han J, Sahota D, et al Maternal serum ADAM12 in Chinese women undergoing screening for aneuploidy in the first trimester. J Matern Fetal Neonatal Med 2010;23(11):1305–1309. doi: 10.3109/14767051003678119.
[33]. Han J, Liu H, Xu ZP, et al Maternal serum PlGF (placental growth factor) in Chinese women in the first trimester undergoing screening for Down syndrome. Eur J Obstet Gynecol Reprod Biol 2016;201:166–170. doi: 10.1016/j.ejogrb.2016.03.046.
[34]. Akolekar R, Syngelaki A, Poon L, et al Competing risks model in early screening for preeclampsia by biophysical and biochemical markers. Fetal Diagn Ther 2013;33(1):8–15. doi: 10.1159/000341264.
[35]. Rolnik DL, Wright D, Poon LC, et al Aspirin versus placebo in pregnancies at high risk for preterm preeclampsia. N Engl J Med 2017;377(7):613–622. doi:10.1056/NEJMoa1704559.
[36]. Roberge S, Bujold E, Nicolaides KH. Aspirin for the prevention of preterm and term preeclampsia: systematic review and metaanalysis. Am J Obstet Gynecol 2018;218(3):287-293.e1. doi: 10.1016/j.ajog.2017.11.561.
[37]. Goodlin RC, Haesslein HO, Fleming J. Aspirin for the treatment of recurrent toxaemia. Lancet 1978;2(8079):51. doi: 10.1016/S0140-6736(78)91367-3.
[38]. Magro-Malosso ER, Saccone G, Di Tommaso M, et al Exercise during pregnancy and risk of gestational hypertensive disorders: a systematic review and meta-analysis. Acta Obstet Gynecol Scand 2017;96(8):921–931. doi: 10.1111/aogs.13151.
[39]. Syngelaki A, Sequeira Campos M, Roberge S, et al Diet and exercise for preeclampsia prevention in overweight and obese pregnant women: systematic review and meta-analysis. J Matern Fetal Neonatal Med 2018;1–161. doi: 10.1080/14767058.2018.1481037.
[40]. Rodger MA, Gris JC, de Vries JIP, et al Low-molecular-weight heparin and recurrent placenta-mediated pregnancy complications: a meta-analysis of individual patient data from randomised controlled trials. Lancet 2016;388(10060):2629–2641. doi: 10.1016/S0140-6736(16)31139-4.
[41]. Roberge S, Demers S, Nicolaides KH, et al Prevention of pre-eclampsia by low-molecular-weight heparin in addition to aspirin: a meta-analysis. Ultrasound Obstet Gynecol 2016;47(5):548–553. doi: 10.1002/uog.15789.
[42]. Conde-Agudelo A, Romero R, Kusanovic JP, et al Supplementation with vitamins C and E during pregnancy for the prevention of preeclampsia and other adverse maternal and perinatal outcomes: a systematic review and metaanalysis. Am J Obstet Gynecol 2011;204(6):503.e1–503.e12. doi: 10.1016/j.ajog.2011.02.020.
[43]. Vadillo-Ortega F, Perichart-Perera O, Espino S, et al Effect of supplementation during pregnancy with L-arginine and antioxidant vitamins in medical food on pre-eclampsia in high risk population: randomised controlled trial. BMJ 2011;342:d2901. doi: 10.1136/bmj.d2901.
[44]. Salles AM, Galvao TF, Silva MT, et al Antioxidants for preventing preeclampsia: a systematic review. ScientificWorldJournal 2012;2012:243476. doi: 10.1100/2012/243476.
[45]. Rumbold A, Ota E, Nagata C, et al Vitamin C supplementation in pregnancy. Cochrane Database Syst Rev 2015;(9):CD004072. doi: 10.1002/14651858.CD004072.pub3.
[46]. Makrides M, Crosby DD, Bain E, et al Magnesium supplementation in pregnancy. Cochrane Database Syst Rev 2014;(4):CD000937. doi: 10.1002/14651858.CD000937.pub2.
[47]. Wen SW, White RR, Rybak N, et al Effect of high dose folic acid supplementation in pregnancy on pre-eclampsia (FACT): double blind, phase III, randomised controlled, international, multicentre trial. BMJ 2018;362:k3478. doi: 10.1136/bmj.k3478.
[48]. Kalafat E, Sukur YE, Abdi A, et al Metformin for the prevention of hypertensive disorders of pregnancy in women with gestational diabetes and obesity: a systematic review and meta-analysis. Ultrasound Obstet Gynecol 2018;52(6):706–714. doi: 10.1002/uog.19084.
[49]. Costantine MM, Cleary K, Hebert MF, et al Safety and pharmacokinetics of pravastatin used for the prevention of preeclampsia in high-risk pregnant women: a pilot randomized controlled trial. Am J Obstet Gynecol 2016;214(6):720e1–e7217. doi: 10.1016/j.ajog.2015.12.038.
[50]. Cluver CA, Hannan NJ, van Papendorp E, et al Esomeprazole to treat women with preterm preeclampsia: a randomised placebo controlled trial. Am J Obstet Gynecol 2018;219(4):388.e1–388.e17. doi: 10.1016/j.ajog.2018.07.019.
[51]. Crandon AJ, Isherwood DM. Effect of aspirin on incidence of pre-eclampsia. Lancet 1979;1(8130):1356. doi: 10.1016/S0140-6736(79)91996-2.
[52]. Beaufils M, Uzan S, Donsimoni R, et al Prevention of pre-eclampsia by early antiplatelet therapy. Lancet 1985;1(8433):840–842. doi: 10.1016/S0140-6736(85)92207-X.
[53]. Askie LM, Duley L, Henderson-Smart DJ, et al Antiplatelet agents for prevention of pre-eclampsia: a meta-analysis of individual patient data. Lancet 2007;369(9575):1791–1798. doi: 10.1016/S0140-6736(07)60712-0.
[54]. Bujold E, Roberge S, Nicolaides KH. Low-dose aspirin for prevention of adverse outcomes related to abnormal placentation. Prenat Diagn 2014;34(7):642–648. doi: 10.1002/pd.4403.
[55]. Wright D, Rolnik DL, Syngelaki A, et al Aspirin for evidence-based preeclampsia prevention trial: effect of aspirin on length of stay in the neonatal intensive care unit. Am J Obstet Gynecol 2018;218(6):612.e1–612.e6. doi: 10.1016/j.ajog.2018.02.014.
[56]. Irgens HU, Reisaeter L, Irgens LM, et al Long term mortality of mothers and fathers after pre-eclampsia: population based cohort study. BMJ 2001;323(7323):1213–1217. doi: 10.1136/bmj.323.7323.1213.
[57]. Riise HK, Sulo G, Tell GS, et al Incident coronary heart disease after preeclampsia: role of reduced fetal growth, preterm delivery, and parity. J Am Heart Assoc 2017;6:e004158. doi: 10.1161/JAHA.116.004158.
[58]. Petersen TG, Liew Z, Andersen AN, et al Use of paracetamol, ibuprofen or aspirin in pregnancy and risk of cerebral palsy in the child. Int J Epidemiol 2018;47(1):121–130. doi: 10.1093/ije/dyx235.
[59]. Henderson JT, Whitlock EP, O’Connor E, et al Low-dose aspirin for prevention of morbidity and mortality from preeclampsia: a systematic evidence review for the U.S. Preventive Services Task Force. Ann Intern Med 2014;160(10):695–703. doi: 10.7326/M13-2844.
[60]. Gilbert RE, Augood C, Gupta R, et al Screening for Down's syndrome: effects, safety, and cost effectiveness of first and second trimester strategies. BMJ 2001;323(7310):423–425. doi: 10.1136/bmj.323.7310.423.
[61]. Ortved D, Hawkins TL, Johnson JA, et al Cost-effectiveness of first-trimester screening with early preventative use of aspirin in women at high risk of early-onset pre-eclampsia. Ultrasound Obstet Gynecol 2019;53(2):239–244. doi: 10.1002/uog.19076.
[62]. Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making 2006;26(6):565–574. doi: 10.1177/0272989X06295361.
[63]. Vickers AJ, Van Calster B, Steyerberg EW. Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests. BMJ 2016;352:i6. doi: 10.1136/bmj.i6.
[64]. Rolnik DL, Wright D, Poon LCY, et al ASPRE trial: performance of screening for preterm pre-eclampsia. Ultrasound Obstet Gynecol 2017;50(4):492–495. doi: 10.1002/uog.18816.
Keywords:

Preeclampsia; First trimester; Screening; Mean arterial pressure; Uterine artery pulsatility index; Placental growth factor

© 2019 by Lippincott Williams & Wilkins, Inc.