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Figure 1.
Analytic Framework
Analytic Framework

Evidence reviews for the US Preventive Services Task Force (USPSTF) use an analytic framework to visually display the key questions that the review will address to allow the USPSTF to evaluate the effectiveness and safety of a preventive service. The questions are depicted by linkages that relate interventions and outcomes. A dashed line indicates health outcomes that follow an intermediate outcome. Further details are available from the USPSTF procedure manual.14

Figure 2.
Literature Flow Diagram
Literature Flow Diagram

NA indicates not applicable.

aDetails about reasons for exclusion are as follows. Relevance: Study aim not relevant. Setting: Study was not conducted in a setting or country relevant to US primary care. Population: Study was not conducted in women and adolescents without a diagnosis of preeclampsia and asymptomatic for the condition. Design: Study did not use an included design. Outcomes: Study did not have relevant outcomes or had incomplete outcomes. Intervention: Study used an excluded intervention/screening approach. Comparator: Study lacked a comparison group. Quality: Study did not meet criteria for fair or good quality. Unable to locate: Library services could not locate article in which study was published.

bIncluded 4 studies (7 articles) on externally validated risk prediction models. Eleven articles were also identified that represent the model development studies related to external validation studies.

Figure 3.
Diagnostic Accuracy of Point-of-Care Tests for Proteinuria (Key Question 4a)
Diagnostic Accuracy of Point-of-Care Tests for Proteinuria (Key Question 4a)

One study49 is not plotted, as it did not provide enough information to construct a 2 × 2 table.

Table 1.  
Differences in Health Outcomes During Pregnancy, at Time of Delivery, or 6 Weeks Postpartum (Key Question 1a and Key Question 5)
Differences in Health Outcomes During Pregnancy, at Time of Delivery, or 6 Weeks Postpartum (Key Question 1a and Key Question 5)
Table 2.  
Index Tests and Reference Standard Characteristics of Included Diagnostic Accuracy Studies (Key Question 4a) Sorted by Index Test and Threshold
Index Tests and Reference Standard Characteristics of Included Diagnostic Accuracy Studies (Key Question 4a) Sorted by Index Test and Threshold
Table 3.  
Study Characteristics of Prospective Cohort Studies Used for External Validation of Preeclampsia Risk Prediction Models (Key Question 2)
Study Characteristics of Prospective Cohort Studies Used for External Validation of Preeclampsia Risk Prediction Models (Key Question 2)
Table 4.  
External Validation Performance of 5 Preeclampsia Risk Prediction Models With Good or Better Discrimination (c Statistic >0.80) (Key Question 2)
External Validation Performance of 5 Preeclampsia Risk Prediction Models With Good or Better Discrimination (c Statistic >0.80) (Key Question 2)
Table 5.  
Overall Summary of Evidence by Key Question
Overall Summary of Evidence by Key Question
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US Preventive Services Task Force
Evidence Report
April 25, 2017

Preeclampsia Screening: Evidence Report and Systematic Review for the US Preventive Services Task Force

Author Affiliations
  • 1Kaiser Permanente Research Affiliates Evidence-based Practice Center, Center for Health Research, Kaiser Permanente, Portland, Oregon
  • 2Oregon Health & Science University, Portland
JAMA. 2017;317(16):1668-1683. doi:10.1001/jama.2016.18315
Abstract

Importance  Preeclampsia is a complex disease of pregnancy with sometimes serious effects on maternal and infant morbidity and mortality. It is defined by hypertension after 20 weeks’ gestation and proteinuria or other evidence of multisystem involvement.

Objective  To systematically review the benefits and harms of preeclampsia screening and risk assessment for the US Preventive Services Task Force.

Data Sources  MEDLINE, PubMed, and Cochrane Central Register of Controlled Trials databases from 1990 through September 1, 2015. Surveillance for new evidence in targeted publications was conducted through October 5, 2016.

Study Selection  English-language trials and observational studies, including externally validated prediction models, of screening effectiveness, benefits, and harms from routine preeclampsia screening during pregnancy.

Data Extraction and Synthesis  Independent dual review of article abstracts and full texts against a priori inclusion criteria. Meta-analysis was not performed because of clinical and statistical heterogeneity of included studies.

Main Outcomes and Measures  Maternal and infant health outcomes, including eclampsia, stroke, stillbirth, preterm birth, and low birth weight; screening and risk prediction test performance; harms of screening and risk assessment.

Results  Twenty-one studies (13 982 participants) were included. No studies directly compared the effectiveness of preeclampsia screening in a screened population vs an unscreened population; 1 US trial (n = 2764) found no difference in benefits or harms with fewer prenatal visits but was underpowered for rare, serious outcomes. For harms, a before-after comparison cohort noninferiority study of urine protein screening for specific indications compared with routine screening (n = 1952) did not identify harms with fewer urine screening tests. Four studies (n = 7123) reported external validation performance of 16 risk prediction models, 5 of which had good or better discrimination (c statistic >0.80) for prediction of preeclampsia, and positive predictive values of 4% in the largest, most applicable validation cohorts. Calibration was not reported despite being a key model performance measure. There were no studies of urine screening test performance conducted in asymptomatic primary care populations; 14 studies of protein urine test performance among women being evaluated for suspected preeclampsia (n = 1888) had wide-ranging test accuracy (sensitivity, 22%-100%; specificity, 36%-100%) and high statistical and clinical heterogeneity in tests used, eligibility criteria, and proteinuria prevalence (8.7%-93.8%).

Conclusions and Relevance  Evidence to estimate benefits and harms of preeclampsia screening and the test performance of different screening approaches over the course of pregnancy was limited. Externally validated risk prediction models had limited applicability and lacked calibration and clinical implementation data needed to support routine use. Further research is needed to better inform risk-based screening approaches and improve screening strategies, given the complex pathophysiology and clinical unpredictability of preeclampsia.

Introduction

Approximately 2% to 8% of pregnancies are affected by preeclampsia, defined by the development of hypertension and proteinuria after 20 weeks’ gestation. In the absence of proteinuria, additional features contribute to diagnosis (ie, thrombocytopenia, renal insufficiency, impaired liver function, pulmonary edema, cerebral or visual symptoms).1 Preeclampsia is the second leading cause of maternal mortality worldwide.2,3 In the United States the rate of preeclampsia increased from 3.4% in 1980 to 3.8% in 2010,4 with the proportion of severe cases also increasing. Identifying women at higher risk for preeclampsia early in pregnancy, based on medical history and routine tests, could inform risk-based prevention and screening. Once preeclampsia is diagnosed, evidence-based interventions may reduce the risk or severity of maternal and infant health outcomes of preeclampsia; these include treatment of high blood pressure, administration of magnesium sulfate to prevent eclampsia, and induced delivery.1,5-12

In 1996, the US Preventive Services Task Force (USPSTF) recommended screening for preeclampsia using office-based blood pressure measurement for all pregnant women at the first prenatal visit and periodically throughout the remainder of the pregnancy (B recommendation).13 The current review was commissioned to systematically review and update evidence on screening for preeclampsia.

Methods
Scope of Review

Detailed methods are available in the full evidence report at https://www.uspreventiveservicestaskforce.org/Page/Document/final-evidence-review153/preeclampsia-screening1. The analytic framework and key questions (KQs) guiding this review are shown in Figure 1.15

Data Sources and Searches

After an initial search for existing systematic reviews and guidelines, a comprehensive search was performed for primary literature in the MEDLINE, PubMed, and Cochrane Central Register of Controlled Trials databases from 1990 through September 1, 2015 (eMethods in the Supplement). Studies published before 1990 were excluded because of changes in diagnostic criteria and treatments in the past 25 years, limiting applicability of earlier evidence.7,11,12 Reference lists of prior reports and publications were also searched. Since September 2015, we continued to conduct ongoing surveillance through article alerts and targeted searches of high-impact journals to identify major studies published in the interim that may affect the conclusions or understanding of the evidence and therefore the related USPSTF recommendation. The last surveillance was conducted on October 5, 2016, and identified no relevant new studies.

Study Selection

Two investigators independently reviewed 10 082 titles and abstracts and 378 full-text articles against prespecified inclusion criteria (Figure 2). Discrepancies were resolved through consensus discussions. English-language, fair- and good-quality studies of pregnant women and adolescents without a diagnosis of preeclampsia and asymptomatic for the condition were included. Studies among women with chronic hypertension, diabetes mellitus, or elevated risk for preeclampsia were also included. Studies were excluded if they solely focused on women seeking high-risk obstetric care, receiving infertility treatment, receiving inpatient care, or if they were conducted in countries not having a high development index designation according to the 2014 United Nations Development Programme.16 Any standard diagnostic criterion for preeclampsia was allowed.1,17,18

Screening interventions included point-of-care tests and clinical tools routinely used in prenatal care to screen for preeclampsia, such as blood pressure measurements using manual or automated devices and point-of-care urine tests for proteinuria with qualitative, quantitative, visual, or automated readings. Only studies using the 24-hour urine test as the reference standard to calculate the diagnostic accuracy of urine protein tests were included. Secondary evaluations and tests used to assess preeclampsia severity or to confirm diagnosis were not included. Evidence on the benefits and harms (KQ1, KQ5) of preeclampsia screening was from randomized clinical trials (RCTs) and observational studies that reported on maternal and infant mortality, morbidity from eclampsia, HELLP (hemolysis, elevated liver enzyme levels, low platelet counts) syndrome, organ damage or failure, fetal growth restriction, preterm delivery, low birth weight, stillbirth, and placental abruption. Evidence was sought on the screening test performance of clinical blood pressure measurement, urinalysis, or both for identifying women with preeclampsia at the time of screening (KQ4), to compare the effectiveness of different screening protocols (eg, instruments, test procedures, timing of tests, rescreen intervals) (KQ4a), to assess the diagnostic accuracy of point-of-care tests for detecting proteinuria (KQ4b), and to evaluate risk-based screening protocols, compared with general screening (KQ4c).

For assessment of preeclampsia risk (KQ2, KQ3), studies evaluating prediction models for use in the first 20 weeks of pregnancy were included to inform and differentiate screening and preventive interventions (eg, aspirin prophylaxis) before preeclampsia develops.19-22 These were externally validated (ie, models tested in another population than the derivation study, assessing either performance or effect) multivariable risk prediction models using patient history and routinely collected clinical measures (eg, body mass index, weight, blood pressure) as well as serum markers and Doppler ultrasound measures (eg, uterine artery pulsatility index).

Quality Assessment and Data Extraction

Two investigators independently assessed the quality of all included studies using criteria predefined by the USPSTF14 and supplemented them with other criteria from the Quality Assessment of Diagnostic Accuracy II for diagnostic accuracy studies (KQ4a)23 and from the Newcastle-Ottawa Scale and Before-After Quality Assessment Tool24 for observational studies (KQ3 and KQ5) (eTable 1 in the Supplement). Each included study received a final quality rating of good, fair, or poor; discrepancies were resolved through discussion. Poor-quality studies (ie, attrition >40%, differential attrition >20%, or other fatal flaws or cumulative effects of multiple minor flaws or missing information significant enough to limit confidence in the validity of results) were excluded. Good-quality studies met all or most of the assessment criteria; fair-quality studies met only some of the assessment criteria.

One investigator abstracted data from all included studies into an Access database (Microsoft Corp). A second investigator checked the data for accuracy.

Data Synthesis and Analysis

Summary evidence tables for each of the key questions include study population characteristics, study design features, and findings. Statistical pooling of results with meta-analysis was not possible for any outcomes because of statistical and clinical heterogeneity due to different study designs, interventions, reference standards, and populations.

Synthesis of included prediction models was informed by methodologic guidance for evaluating performance of multivariable risk prediction models.25-29 Model performance was evaluated based on commonly recognized metrics. These include discrimination (c statistic), or area under a receiver operating characteristic curve plot, representing the probability that a case will have a higher risk score than a noncase. Sensitivity, specificity, positive predictive values (PPVs), and negative predictive values also measure discrimination. A priori risk-level cutpoints are optimal, but in the preeclampsia prediction literature “detection rates,” analogous to sensitivity, were commonly reported, with risk cutpoints corresponding to a 10% false-positive rate (90% specificity).27 Calibration reflects the extent to which the model predictions match the observed outcomes for individuals across different risk levels; goodness-of-fit tests (eg, Hosmer-Lemeshow test) are sometimes reported, but calibration plots that graphically depict the observed outcome frequencies against predicted probabilities are more informative.28 Discrimination and calibration are both necessary for evaluating model performance in validation studies.28 The models we identified with good or better discrimination based on the c statistic (≥0.80)30 are described in this review. Models were classified as to whether they aimed to predict preeclampsia requiring early delivery (<34 weeks’ gestation) or a later-onset diagnosis (≥34 weeks’ gestation).

Results

Twenty-one included studies comprising 13 982 participants and reported in 35 publications were identified (Figure 2).31-65 No studies directly compared the effectiveness of preeclampsia screening in a screened population vs an unscreened population (KQ1). One RCT31 (n = 2764) on the benefits and harms of a reduced prenatal visit schedule (KQ1a, KQ5) and 1 observational before-after study (n = 1952) for potential harms of an indicated rather than routine protein urine screening protocol (KQ5)50 were included. Four external validation studies (n = 7123) evaluating 1 or more multivariable models for predicting preeclampsia risk (16 models total, 5 with good or better discrimination) were included (KQ2).32-35 A single observational study (n = 255) evaluating the harms of risk prediction (KQ3) was included.36 No studies evaluated the overall, protocol-specific, or risk-based effectiveness of screening tests for identifying women with preeclampsia (KQ4, KQ4b, KQ4c). Although no studies of the test accuracy of proteinuria screening were found among general prenatal care populations (KQ4a), 14 studies (n = 1888) examining the diagnostic accuracy of urine tests for proteinuria among women being evaluated for suspected preeclampsia were included to approximate test performance.37-49,54

Screening Effectiveness

Key Question 1a. Does preeclampsia screening effectiveness differ by screening protocol (eg, tests used, timing of tests, rescreen intervals) or preeclampsia risk status?

One fair-quality RCT conducted from 1992 to 1994 in a large managed care organization randomized 2764 pregnant women ages 18 to 39 presenting for prenatal care to a routine number of prenatal care visits (14 visits) or a schedule of fewer visits (9 visits) (eTable 2 in the Supplement).31 A total of 2328 women completed the study: 1163 in the control group and 1165 in the intervention group. The study enrolled women at low risk for preeclampsia presenting for prenatal care before 13 weeks’ gestation. Routine prenatal care consisted of visits that included screening for preeclampsia with blood pressure measurement and point-of-care proteinuria testing every 4 weeks between 8 and 28 weeks’ gestation, then every 2 weeks until 36 weeks’ gestation, then weekly until delivery for a total of 14 prenatal care visits. For the intervention, the study aimed to reduce the number of visits to 9 (at 8, 12, 16, 24, 28, 32, 36, 38, and 40 weeks of gestation). At baseline, there were no statistically significant differences between groups on maternal characteristics. During pregnancy, women in the control group had more health care visits in total (P < .001) than women in the intervention group, but the mean difference in the number of visits between the 2 study groups was smaller than intended (12.0 [SD, 4.2] vs 14.7 [SD, 4.2]; P < .001) (Table 1). There were no statistically significant differences between groups on maternal health outcomes (eg, gestational diabetes, preeclampsia), delivery complications (eg, preterm delivery, cesarean delivery, postpartum hemorrhage), or neonatal outcomes (eg, birth weight, gestational age, stillbirth).

Screening Harms

Key Question 5. What are the harms of preeclampsia screening, and do they differ by risk status or screening protocol?

The same fair-quality trial (n = 2764) included for KQ1a found no difference in birth outcomes (eg, low birth weight, preterm birth, number of cesarean deliveries) with an intended reduction in the number of prenatal care visits (eTable 2 in the Supplement).31 Power was insufficient to detect differences for rare outcomes related to preeclampsia, particularly serious adverse maternal events such as progression to eclampsia, organ failure, stroke, and death.

An additional fair-quality retrospective before-and-after comparison cohort study (n = 1952) evaluated differences in health outcomes after a change in practice at a hospital-based nurse midwifery practice that primarily served low-income Hispanic women (74% of eligible study participants). The practice change was from routine prenatal dipstick urine testing to “clinically indicated” urine testing (eTable 5 in the Supplement).50 All women in the study received urine tests at their first prenatal visit; those delivered before August 15, 2002 (n = 933), received routine urine screening with chemical reagent strips testing for bacteria or protein at all subsequent visits, whereas those delivered after August 15, 2002 (n = 1019), had subsequent urine screening only for certain conditions. Indications for urine testing were symptoms of a urinary tract infection, severe vomiting, weight loss of 0.9 kg or more since the previous visit, systolic blood pressure 140 mm Hg or higher, diastolic blood pressure 90 mm Hg or higher, or a health condition requiring periodic urine testing (eg, chronic hypertension, renal disease). Women in the routine urine testing group had used an average of 7.8 (range, 0-19) tests, whereas women in the indicated testing group had used an average of 1.4 (range, 0-16). Among the indicated testing group, the reasons for urine testing were urinary tract infection or vaginitis symptoms (31.5%) and elevated blood pressure or significant preeclampsia-related symptoms (35.6%).

The purpose of the study was to evaluate whether changes in the urine screening approach were safe; thus, statistical tests were designed to evaluate noninferiority—statistically significant P values indicated no difference between the 2 groups (Table 1). The study reported equivalence in the rates of diagnosis for preeclampsia/eclampsia, high blood pressure, and cesarean deliveries. Preterm delivery was not equivalent between groups, but the rate was higher in the routine testing group, supporting the noninferiority of indicated testing.

Similar to the evidence on benefits, for harms the absence of adequately powered studies, conducted more recently in broader prenatal care populations, limits the conclusions that can be drawn to evaluate preeclampsia screening protocols.

Accuracy of Screening Tests

Key Question 4a. How accurate are different point-of-care screening tests for proteinuria (a diagnostic criterion for preeclampsia)?

Fourteen studies (n = 1888) examined the diagnostic accuracy of urine tests for proteinuria among women being evaluated for suspected preeclampsia on the basis of positive point-of-care urine test results, high blood pressure, symptoms, or for undefined reasons (eTable 4 in the Supplement).37-49,54 Six studies were conducted in the United States,38,39,43,44,48,49 4 in the United Kingdom,37,42,46,47 1 in New Zealand,40 1 in Canada,41 1 in Chile,54 and 1 in the Netherlands.45

Twelve of the studies evaluated the accuracy of urine tests for protein to creatinine ratio (Table 2) in 1516 pregnant women.37-45,48,49,54 The test sensitivities ranged from 65% (95% CI not calculable)49 to 96% (95% CI, 88%-99%),45 with most falling above 81% (Figure 3). Limited information on the specific protein to creatinine ratio index test used, differing test thresholds, and diverse study enrollment criteria, along with the dispersion of study data points, account for considerable clinical and statistical heterogeneity for diagnostic accuracy. Summary conclusions about overall performance could not be drawn.

Two studies evaluated the accuracy of urine tests for albumin to creatinine ratio using the DCA 2000 point-of-care system (Bayer Healthcare) in 321 pregnant women40,47 (Table 2). The sensitivities were high (>90%), but specificities differed (Figure 3). In 1 study with high proteinuria prevalence47 (45%), specificity remained high (>90%), but in the study with lower proteinuria prevalence 40 (8.7%), specificity was lower (<70%).

Four studies evaluated the accuracy of protein urine dipsticks in 634 pregnant women with mixed test performance characteristics.39,40,46,47 The studies used dipsticks of different makes and models (Table 2), but all studies used the same reference standard. Sensitivities ranged from 22% to 100% and specificities from 36% to 100% (Figure 3). One dipstick test in a good-quality, high-proteinuria prevalence study47 had both sensitivity and specificity above 80% for automated reading (with Clinitek 50) of the Multistix 8SG dipstick.47 All other studies had very high sensitivity and low specificity or vice versa.

Likely owing to diversity of index tests used, study eligibility criteria, and proteinuria prevalence, there was considerable variation in performance of urine screening tests for protein. No evidence was found to estimate the accuracy of urine protein screening tests among healthy prenatal populations.

Risk Prediction

Key Question 2. What is the effectiveness of risk prediction in early pregnancy for identifying women at high risk for preeclampsia?

Four external validation studies (n = 7123) reported on the performance of 16 distinct risk prediction models in 7 articles (Table 3).32-35,51-53 The outcomes differed: 6 models were developed for prediction of preeclampsia requiring delivery before 34 weeks of gestation,55,57,59-62 1 before 37 weeks of gestation,58 7 after 34 weeks of gestation,55,56,60,62-65 and 2 predicting any preeclampsia.58,63 Preterm preeclampsia is rare, so outcome prevalence was for models predicting later or any preeclampsia. An additional 11 articles reported on the model development studies related to these external validations.55-65 Five of the externally validated models had c statistics indicating good or better discrimination (≥0.80) (Table 4).55-58,66 The models were labeled with lead authors of the model development studies cited in external validation. Most of the included models were developed in the United Kingdom, with overlap in the investigators and funding source.

The models were validated with prospective cohort data collected in the United States by Oliveira et al (n = 2962),33 Australia by Park et al (n = 3014),34 Italy by Farina et al (n = 554),32 and Norway by Skråstad et al (n = 541).35 The timing of risk calculation occurred before 20 weeks’ gestation for all models but varied depending on the gestation at which women presented and on the availability of variables needed for the model. The validation studies by Farina et al and Park et al enrolled women with singleton pregnancies presenting for aneuploidy screening; the validation study by Oliveira et al enrolled women with singleton pregnancies presenting for prenatal care in the first trimester; and the validation study by Skråstad et al enrolled nulliparous women, resulting in a slightly younger cohort (mean age, 26 years). All of the cohorts were enrolled sometime between 2007 and 2012.

The validation cohort study33 most applicable to US primary care settings enrolled average-risk women presenting for prenatal care in the first trimester at 4 health centers in Baltimore, Maryland, and was used to evaluate a model by Poon et al (early preeclampsia)55 and the model by Odibo et al.57 The model by Poon et al55 was the only one externally validated in more than 1 setting including the United States.33,34 In the US validation study (n = 2833),33 discrimination was moderate (c statistic, 0.80 [95% CI, 0.71-0.89]), and detection (52%) and PPV (4.2) were low, based on 29 cases (1% incidence); in the Australian validation cohort of women with singleton pregnancies attending aneuploidy screening (n = 3014),34 discrimination was high (c statistic, 0.93 [95% CI, 0.92-0.94]), as was detection (91.7% [95% CI, 61.5-98.6]), but the PPV was low (3.6), based on only 12 cases.

The model by Odibo et al57 had better discrimination and detection in the US validation cohort and had been developed in a US population. The model used clinical history, placental protein 13, pregnancy-associated plasma protein A, and the mean artery pulsatility index to predict preeclampsia-required delivery before 34 weeks’ gestation (c statistic, 0.86 [95% CI, 0.73-0.99]). The model was validated with a smaller subset of the US cohort (n = 871; 29% of the 2969 women in the external validation cohort33), because not all women had data on a serum marker needed for the model.

The model developed by Akolekar et al58,66 and validated by Skråstad et al35 was used to predict any preeclampsia requiring delivery before 37 weeks’ gestation (c statistic, 0.94 [95% CI, 0.86-1.00]). There were 5 cases of early preeclampsia requiring delivery (incidence, 0.9%). Detection was 80%, and the PPV was 6.8. Two additional models used clinical history and uterine Doppler measures to detect later-onset preeclampsia, a more common outcome. These models, by Onwudiwe et al56 and Poon et al (late preeclampsia),55 had good or better discrimination, detection of 85% and 74%, and PPVs of 39.3 and 36.3, respectively, when validated in a small Italian cohort study (n = 554).32

Information on model calibration was not provided in any of the external validation studies, precluding a complete assessment of model performance. There were no randomized impact studies evaluating the health benefits or harms of risk assessment using multivariable prediction models compared with standard care.

Key Question 3. What are the harms of preeclampsia risk prediction?

One fair-quality, prospective cohort study (n = 255) conducted in Spain examined whether first-trimester risk prediction and clinical care based on risk status increased anxiety in pregnant women (eTable 3 in the Supplement).36 Risk for early preeclampsia requiring delivery before 34 weeks was assessed using a model developed in Spain and with modest performance in the US-based validation study.33 Pregnant women screened as high risk were recruited and matched with the next visiting low-risk screened woman in a first trimester screening unit (135 low risk, 120 high risk). After risk prediction, women received counseling on potential risks of preeclampsia. Women at high risk were followed up with a protocol that included recommended daily intake of aspirin (150 mg) from the day of screening until 36 weeks’ gestation and second-trimester ultrasonography at 20 to 22 weeks.36 Low- and high-risk women did not differ in anxiety, measured with the Spielberg State-Trait Anxiety Inventory, at baseline or after risk prediction and counseling.36 First-trimester preeclampsia risk prediction and counseling was not associated with greater maternal anxiety in the immediate short term when coupled with counseling and potentially preventive medication. The risk assessment model used and the content of the counseling were not well described, and the results may have limited generalizability.

Discussion

This review identified only 1 RCT, conducted more than 20 years ago, that compared different screening strategies and found no difference in benefits or harms from slightly fewer preeclampsia screening visits compared with the standard of care at the time.31 The applicability of these findings to current practice settings and populations is limited, given changes to screening, diagnosis, and management practices, as well as population health, over the past 2 decades (Table 5). An observational study published in 2007 found no harms associated with indicated rather than routine urine testing for preeclampsia screening, but study design and setting limit applicability. Both of these studies were underpowered to assess very rare adverse events associated with preeclampsia, particularly serious maternal risks from eclampsia and stroke.

No studies directly evaluated the individual or combined test accuracy of blood pressure screening and urine protein screening for detecting the presence or absence of preeclampsia at a single point in time or cumulatively across pregnancy. Evidence to estimate the frequency of false-positive and false-negative readings for elevated blood pressure and proteinuria was not found. Understanding the optimal use of low-resource and relatively noninvasive screening and confirmatory tests (eg, additional blood pressure measurements, repeat point-of-care urine testing, diagnostic urine testing) has likely been a lower priority research question than those concerned with etiology and treatment of preeclampsia. Studies of current prenatal care populations, with a higher prevalence of obesity and other preeclampsia risk factors, are needed to derive more complete evidence-based approaches to preeclampsia screening. This is particularly important in the context of recent changes to diagnostic criteria that support additional tests for women with hypertension in the absence of proteinuria.68

This review did not include evidence on associations of blood pressure and proteinuria levels and the likelihood of developing preeclampsia later in the pregnancy. Such studies are important for establishing diagnostic criteria and identifying candidate markers for risk prediction but do not address the question of screening effectiveness, which this review aimed to evaluate. Chronic hypertension is associated with increased probability of developing preeclampsia,69 and high blood pressure occurring for the first time during pregnancy is one of the diagnostic criteria for preeclampsia.1 Thus, the current clinical practice of repeat measurement at clinical visits remains important for all pregnant women. The accuracy of individual blood pressure readings is optimized if conducted in accordance with guidance on clinical blood pressure measurement in general70 and during pregnancy.71,72

Associations between proteinuria levels and adverse preeclampsia outcomes are less consistent.73,74 Recognizing this, updated American College of Obstetricians and Gynecologists (ACOG) guidelines address other signs and symptoms that may be used to diagnose preeclampsia in the absence of proteinuria, including cerebral or visual symptoms, impaired liver or renal function, low platelet count, and pulmonary edema.1 These changes to diagnostic criteria could increase the number of women identified with preeclampsia, require different approaches to diagnostic confirmation, and may lead to the development of new approaches to screening. Regardless of these changes, the presence of significant proteinuria remains a key diagnostic criterion for preeclampsia. Due to historical precedent and low resource requirements, urine dipstick testing is likely to continue, despite its recognized poor and variable test performance75 (particularly with visual rather than automated readings47,76).

This review and others74,77,78 identified a larger body of evidence on the performance of protein to creatinine ratio spot tests for detecting significant proteinuria. The high variability in the populations, tests evaluated, and accuracy limits conclusions that can be drawn regarding the optimal clinical application of these tests. Guidance from ACOG suggests that diagnosis can be based on the 24-hour protein test (>300 mg) or protein to creatinine ratio (>0.30). Guidance on the most accurate proteinuria screening approach is not provided by ACOG. Current evidence is not from a general screening population; rather, it is from among women with suspected preeclampsia and aims to determine whether protein to creatinine ratio spot tests are accurate enough to substitute for the more resource-intensive 24-hour collections, the reference standard for diagnosis of proteinuria in pregnancy.74,77 The applicability of these results to point of care screening is limited. Urine tests for protein are conducted throughout pregnancy but practices may vary, as this is not a clinical standard per se but rather a long-standing practice tradition. False-positive results lead to further confirmatory testing and heightened surveillance. Maximizing single-test performance for a relatively inexpensive and noninvasive test may have limited value. Evidence on test performance in general prenatal care populations with repeat testing, and comparative studies of different approaches to screening, could better define the optimal role for point-of-care urine testing in routine preeclampsia screening or diagnostic evaluation.

This review sought multivariable risk prediction models that could be used for risk-based screening or for targeting other clinical preventive services, such as aspirin chemoprophylaxis for preeclampsia prevention.22 Five of the 16 externally validated multivariable risk prediction models identified had good or better discrimination and PPVs ranging from 4% to 39%. Information on model calibration was not provided for any of the models, limiting evaluation of the likely performance or effect of clinical application. Moreover, serum markers and Doppler measures may not be routinely collected, limiting their feasibility for routine primary care risk assessment. Recent systematic reviews,79,80 several methodological critiques,26,81-83 and recent guidance from ACOG84 support the findings of this review on the evidence limitations and absence of a well-supported model to be used in routine prenatal care for prediction of preeclampsia risk.

Evidence on the net effect of risk prediction and the clinical actions that follow identification of a woman at risk for preeclampsia is needed to fully evaluate the effect of clinical risk prediction.85 High sensitivity may be more important for prediction of preeclampsia risk, because false-negative results arguably are more detrimental than false-positive results82; a lower risk threshold and lower PPV may be reasonable86 to consider for low-dose aspirin prophylaxis and heightened surveillance.87 Evidence is limited for determining whether model-based risk prediction would be beneficial for preeclampsia health outcomes, beyond risk-assessment approaches currently practiced by clinicians.80,85,88,89 Rigorous validation and well-designed clinical impact studies are needed to determine the likely performance and effect on health outcomes for multivariable risk assessment models.

Limitations

The review was limited to externally validated models, a minimum level of evidence necessary for estimating performance of a model before considering routine use. Quality appraisal of prediction models was not conducted as part of the synthesis. The risk of bias inherent to model development studies is addressed to some extent with external validation and impact studies, so this review focused on this higher level of evidence.

The relatively short time frame of pregnancy, rarity and unpredictability of severe preeclampsia, and interwoven maternal and fetal risks pose challenges to straightforward estimation of screening performance, benefits, and harms. No studies were identified on the effectiveness of screening for preeclampsia, including risk-based approaches to care. No studies assessing the accuracy of urine protein testing in general prenatal care populations or of the common practice of repeated testing over the course of pregnancy were identified. Consideration of different approaches to screening among women with hypertension in the absence of proteinuria may be important for future reviews as more evidence becomes available on the clinical use of newer diagnostic criteria. Large study populations are required to compare different approaches to screening and effects on maternal and perinatal health outcomes, as well as longer-term sequelae.

The need to evaluate the proportion of women misclassified as having or not having preeclampsia at a single point or over the course of pregnancy may not be clinically important when the result of a false-negative finding is to continue screening and when the result of a false-positive finding is enhanced surveillance and additional noninvasive diagnostic tests. Trials of different approaches to screening would provide more informative data for improving clinical screening practices and preeclampsia outcomes. The absence of information on potential harms of risk prediction, considering the high false-positive rates, is a notable shortcoming of the risk prediction literature. Without comparisons of proposed models to current clinical practices, the potential benefits and harms of risk prediction cannot be determined. Testing different prenatal care algorithms against usual care, possibly incorporating use of the best-performing and most feasible models, would be valuable.

Many of the studies identified had very few cases to classify, so the confidence intervals for performance estimates were wide. Shortcomings in the literature on preeclampsia prediction related to transparency and completeness of reporting modeling have been noted by others.26,79 The absence of calibration statistics limited the ability to comprehensively evaluate and compare model performance.29,81 Values of area under the curve do not provide a solid basis for determining how well, and at what level of risk, a risk prediction model would perform.90

Conclusions

Evidence to estimate benefits and harms of preeclampsia screening and the test performance of different screening approaches over the course of pregnancy was limited. Externally validated risk prediction models had limited applicability and lacked calibration and clinical implementation data needed to support routine use. Further research is needed to better inform risk-based screening approaches and improve screening strategies, given the complex pathophysiology and clinical unpredictability of preeclampsia.

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Article Information

Corresponding Author: Jillian T. Henderson, PhD, Kaiser Permanente Research Affiliates Evidence-based Practice Center, Center for Health Research, Kaiser Permanente Northwest, 3800 N Interstate Ave, Portland, OR 97227 (jillian.t.henderson@kpchr.org).

Author Contributions: Dr Henderson had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Henderson, Burda.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Burda.

Administrative, technical, or material support: Thompson, Burda, Cantor.

Supervision: Henderson.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.

Funding/Support: This research was funded under contract HHSA-290-2012-00151-I, Task Order 4, from the Agency for Healthcare Research and Quality (AHRQ), US Department of Health and Human Services, under a contract to support the USPSTF.

Role of the Funder/Sponsor: Investigators worked with USPSTF members and AHRQ staff to develop the scope, analytic framework, and key questions for this review. AHRQ had no role in study selection, quality assessment, or synthesis. AHRQ staff provided project oversight; reviewed the report to ensure that the analysis met methodological standards; and distributed the draft for peer review. Otherwise, AHRQ had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript findings. The opinions expressed in this document are those of the authors and do not reflect the official position of AHRQ or the US Department of Health and Human Services.

Additional Contributions: We gratefully acknowledge the following individuals for their contributions: AHRQ staff; the US Preventive Services Task Force; and EPC staff Evelyn P. Whitlock, MD, MPH, Jennifer Lin, MD, Tracy Beil, MPH, Smyth Lai, MLS, and Elizabeth Hess, ELS(D). USPSTF members, peer reviewers, and federal partner reviewers did not receive financial compensation for their contributions.

Additional Information: A draft version of this evidence report underwent external peer review from 4 content experts (Gregory E. Simon, MD, Group Health Research Institute; Barbara Yawn, MD, Department of Research, Olmsted Medical Center; Marian McDonagh, PharmD, Oregon Health and Science University; Ramin Mojtabai, MD, John Hopkins Bloomberg School of Public Health) and 4 federal partners (Centers for Disease Control and Prevention, National Institute of Mental Health, Substance Abuse and Mental Health Services Administration, and the US Air Force). Comments were presented to the USPSTF during its deliberation of the evidence and were considered in preparing the final evidence review.

Editorial Disclaimer: This evidence report is presented as a document in support of the accompanying USPSTF Recommendation Statement. It did not undergo additional peer review after submission to JAMA.

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