Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models

The role and mechanism of various trace elements in atherosclerosis

Atherosclerosis is a slow and complex disease that involves various factors, including lipid metabolism disorders, oxygen-free radical production, inflammatory cell infiltration, platelet adhesion and aggregation, and local thrombosis. Trace elements play a crucial role in human health. Many trace elements, especially metallic ones, not only maintain the normal functions of organs but also participate in basic metabolic processes. The latest studies have revealed a close correlation between trace elements and the occurrence and progression of atherosclerosis. The imbalance of these trace elements can induce atherosclerosis or accelerate its progression through various mechanisms, which poses a significant threat to human health. Therefore, exploring the specific mechanism of trace elements on atherosclerosis is highly significant. In this review, we summarized the roles and mechanisms of iron, copper, zinc, magnesium, and selenium homeostasis and imbalance in atherosclerosis development, in order to identify novel targets and therapeutic strategies for treating atherosclerosis.

Prediction of adverse maternal and perinatal outcomes associated with pre-eclampsia and hypertensive disorders of pregnancy: a systematic review and meta-analysis

Background

Hypertensive disorders of pregnancy are a leading cause of maternal and perinatal morbidity and mortality. If women at high risk for developing complications could be identified early, level of care could be triaged, limited resources could be correctly allocated and targeted interventions to prevent complications could be implemented.

Methods

We updated a systematic review and meta-analysis and added single outcomes. Women with hypertensive disorders of pregnancy were included. Exposures were tests predicting adverse maternal and/or perinatal outcomes. We searched Medline, Embase, CINAHL, and Cochrane library from January 2016-February 2024. We included studies identified from the previous review. We calculated effect measures. For similar predictive tests and outcomes, area under the receiver-operating-characteristic curve (AUROC) were pooled. This study was registered by PROSPERO: CRD42022336368.

Findings

Of the 2898 studies identified, 80 were included. Thirty were added from the previous review resulting in 110 included studies with 506,178 women. Despite more than 1500 tests being performed, most outcomes could not be pooled due to heterogeneity in populations, tests, and outcome definitions. For maternal outcomes, only studies reporting on the Pre-eclampsia Integrated Estimate of RiSk (fullPIERS) model could be pooled. For the composite outcome within 48-h the AUROC was 0.78 (95% CI 0.71-0.86, N = 8). There was significant heterogeneity (I 2  = 95.7%). For perinatal outcomes, data were pooled for pulsatility index in the umbilical artery and soluble FMS-like tyrosine kinase-1 (sFlt-1)/placental growth factor (PlGF) ratio. Biomarkers like the sFlt-1/PlGF ratio showed promising predictive performance for some outcomes but were not externally validated.

Interpretation

Despite including over 100 studies with more than 1500 predictors, we were unable to pool any single maternal outcomes and only a few individual perinatal outcomes. The fullPIERS model was externally validated, showing moderate accuracy which varied across studies and should be validated in each new population. Angiogenic biomarkers showed promise but need validation. Future studies should use standardized outcome measures and validate promising tests.

Funding

VB is supported by the Swedish Research Council, Grant number 2020-01481. University of Gothenburg.

Machine learning-enabled maternal risk assessment for women with pre-eclampsia (the PIERS-ML model): a modelling study

BACKGROUND

Affecting 2-4% of pregnancies, pre-eclampsia is a leading cause of maternal death and morbidity worldwide. Using routinely available data, we aimed to develop and validate a novel machine learning-based and clinical setting-responsive time-of-disease model to rule out and rule in adverse maternal outcomes in women presenting with pre-eclampsia.

METHODS

We used health system, demographic, and clinical data from the day of first assessment with pre-eclampsia to predict a Delphi-derived composite outcome of maternal mortality or severe morbidity within 2 days. Machine learning methods, multiple imputation, and ten-fold cross-validation were used to fit models on a development dataset (75% of combined published data of 8843 patients from 11 low-income, middle-income, and high-income countries). Validation was undertaken on the unseen 25%, and an additional external validation was performed in 2901 inpatient women admitted with pre-eclampsia to two hospitals in south-east England. Predictive risk accuracy was determined by area-under-the-receiver-operator characteristic (AUROC), and risk categories were data-driven and defined by negative (-LR) and positive (+LR) likelihood ratios.

FINDINGS

Of 8843 participants, 590 (6·7%) developed the composite adverse maternal outcome within 2 days, 813 (9·2%) within 7 days, and 1083 (12·2%) at any time. An 18-variable random forest-based prediction model, PIERS-ML, was accurate (AUROC 0·80 [95% CI 0·76-0·84] vs the currently used logistic regression model, fullPIERS: AUROC 0·68 [0·63-0·74]) and categorised women into very low risk (-LR <0·1; eight [0·7%] of 1103 women), low risk (-LR 0·1 to 0·2; 321 [29·1%] women), moderate risk (-LR >0·2 and +LR <5·0; 676 [61·3%] women), high risk (+LR 5·0 to 10·0, 87 [7·9%] women), and very high risk (+LR >10·0; 11 [1·0%] women). Adverse maternal event rates were 0% for very low risk, 2% for low risk, 5% for moderate risk, 26% for high risk, and 91% for very high risk within 48 h. The 2901 women in the external validation dataset were accurately classified as being at very low risk (0% with outcomes), low risk (1%), moderate risk (4%), high risk (33%), or very high risk (67%).

INTERPRETATION

The PIERS-ML model improves identification of women with pre-eclampsia who are at lowest and greatest risk of severe adverse maternal outcomes within 2 days of assessment, and can support provision of accurate guidance to women, their families, and their maternity care providers.

FUNDING

University of Strathclyde Diversity in Data Linkage Centre for Doctoral Training, the Fetal Medicine Foundation, The Canadian Institutes of Health Research, and the Bill & Melinda Gates Foundation.

Diagnostic Approach to Elevated Liver Function Tests during Pregnancy: A Pragmatic Narrative Review

Liver disease is not uncommon during pregnancy and is associated with increased maternal and fetal/neonatal morbidity and mortality. Physiological changes during pregnancy, including a hyperestrogenic state, increase in circulating plasma volume and/or reduction in splanchnic vascular resistance, and hemostatic imbalance, may mimic or worsen liver disease. For the clinician, it is important to distinguish among the first presentation or exacerbation of chronic liver disease, acute liver disease non-specific to pregnancy, and pregnancy-specific liver disease. This last group classically includes conditions such as hyperemesis gravidarum, intrahepatic cholestasis of pregnancy, liver disorders associated with the pre-eclampsia spectrum, and an acute fatty liver of pregnancy. All of these disorders often share pathophysiological mechanisms, symptoms, and laboratory findings (such as elevated liver enzymes), but a prompt and correct diagnosis is fundamental to guide obstetric conduct, reduce morbidity and mortality, and inform upon the risk of recurrence or development of other chronic diseases later on in life. Finally, the cause of elevated liver enzymes during pregnancy is unclear in up to 30-40% of the cases, and yet, little is known on the causes and mechanisms underlying these alterations, or whether these findings are associated with worse maternal/fetal outcomes. In this narrative review, we aimed to summarize pragmatically the diagnostic work-up and the management of subjects with elevated liver enzymes during pregnancy.

EASL Clinical Practice Guidelines on the management of liver diseases in pregnancy

Liver diseases in pregnancy comprise both gestational liver disorders and acute and chronic hepatic disorders occurring coincidentally in pregnancy. Whether related to pregnancy or pre-existing, liver diseases in pregnancy are associated with a significant risk of maternal and fetal morbidity and mortality. Thus, the European Association for the Study of Liver Disease invited a panel of experts to develop clinical practice guidelines aimed at providing recommendations, based on the best available evidence, for the management of liver disease in pregnancy for hepatologists, gastroenterologists, obstetric physicians, general physicians, obstetricians, specialists in training and other healthcare professionals who provide care for this patient population.

Prediction of adverse neonatal outcome at admission for early-onset preeclampsia with severe features

BACKGROUND

Preeclampsia remains the leading cause of maternal morbidity and mortality. Consequently, research has focused on validating tools to predict maternal outcomes regarding clinical and biochemical features from the maternal compartment. However, preeclampsia also leads to neonatal complications due to placental insufficiency and prematurity, being the early-onset type associated with the poorest outcome. Hence, it is imperative to study whether these existing tools can predict adverse neonatal outcome.

OBJECTIVE

To assess the predictive value for adverse neonatal outcome of Doppler ultrasound, angiogenic factors and multi-parametric risk-score models in women with early-onset severe preeclampsia.

STUDY DESIGN

This is a prospective cohort study of consecutive singleton pregnancies complicated by early-onset (developed before 34 week's gestation) severe preeclampsia.

RESULTS

63 women with early-onset severe preeclampsia, 18 (28.6%) presented an adverse neonatal outcome. Placental growth factor (PlGF) showed the best discrimination between neonatal outcomes among angiogenic factors. PREP-L score is a multi-parametric risk-score for the prediction of complications in early-onset preeclampsia which includes maternal characteristics and clinical and analytical data obtained at admission. Good predictive values for the prediction of neonatal complications were found with the combination of PREP-L score with advanced Doppler (AUC ROC 0.9 95% CI 0.82-0.98]) and with PlGF levels (AUC ROC 0.91 [95% CI 0.84-0.98]).

CONCLUSIONS

The combination of maternal risk scoring (PREP-L score) with angiogenic factors or fetal Doppler ultrasound at the time of diagnosis of early-onset preeclampsia with severe features performs well in predicting adverse neonatal outcome.

Preterm and term pre-eclampsia: Relative burdens of maternal and perinatal complications

OBJECTIVE

To determine the relative burdens of maternal and perinatal complications for preterm and term pre-eclampsia.

DESIGN

Prospective observational cohort study.

SETTING

Two English maternity units.

POPULATION

Unselected women with singleton pregnancies who developed pre-eclampsia (International Society for the Study of Hypertension in Pregnancy definition).

METHODS

Outcomes were ascertained by health record review and compared between pregnancies with preterm (versus term) pre-eclampsia.

MAIN OUTCOME MEASURES

Severe maternal hypertension, maternal mortality or major maternal morbidity, perinatal mortality or major neonatal morbidity, neonatal unit (NNU) admission ≥48 hours, and birthweight <3rd percentile.

RESULTS

Among 40 241 singleton pregnancies, 298 (0.7%, 95% confidence interval [CI] 0.66-0.83) and 1194 (3.0%, 95% CI 2.8-3.1) developed preterm and term pre-eclampsia, respectively. Women with preterm (versus term) pre-eclampsia more commonly experienced adverse maternal or perinatal events: severe hypertension 18.5% (95% CI 14.5-23.3) versus 13.6% (95% CI 11.7-15.6); maternal mortality/major morbidity 7.4% (95% CI 4.9-10.9) versus 2.2% (95% CI 1.5-3.2); perinatal mortality/major neonatal morbidity 29.5% (95% CI 24.6-34.9) versus 2.2% (95% CI 1.5-3.2); and birthweight <3rd percentile 54.4% (95% CI 48.7-59.9) versus 14.2% (95% CI 12.4-16.3). However, in absolute terms, most maternal complications occurred in women with term pre-eclampsia, as did a large proportion of perinatal complications: severe hypertension 74.7% (95% CI 68.5-80.0); maternal mortality/major morbidity 54.2% (95% CI 40.3-67.4); perinatal mortality/major neonatal morbidity 22.8% (95% CI 16.1-31.3); NNU admission ≥48 hours 38.1% (95% CI 32.4-44.1); and birthweight <3rd percentile 51.2% (95% CI 45.8-56.5).

CONCLUSIONS

Although adverse event risks are greater with preterm (versus term) pre-eclampsia, term disease is associated with at least equivalent total numbers of maternal, and a significant proportion of perinatal, adverse events. Increased efforts should be made to decrease the incidence of term pre-eclampsia.

Similar Pro- and Antiangiogenic Profiles Close to Delivery in Different Clinical Presentations of Two Pregnancy Syndromes: Preeclampsia and Fetal Growth Restriction

The purpose of this study was to evaluate serum levels of anti- and pro-angiogenic substances measured using enzyme-linked immunosorbent assays and their ratios in pregnancies complicated by different clinical subsets of placental ischemic syndrome: preeclampsia and/or fetal growth restriction. A prospective case-control study was performed consisting of 77 singleton pregnancies complicated by preeclampsia, preeclampsia with concurrent fetal growth restriction (FGR), and isolated normotensive FGR pairwise matched by gestational age with healthy pregnancies. The entire study cohort was analyzed with respect to adverse pregnancy outcomes that occurred. In all investigated subgroups, placental growth factor (PlGF) was lower and soluble endoglin (sEng), the soluble fms-like tyrosine kinase-1-sFlt-1/PlGF and sFlt-1*sEng/PlGF ratios were higher than in the control group. The differences were most strongly pronounced in the PE with concurrent FGR group and in the sFlt-1/PlGF ratio. The highest sFlt-1 values in preeclamptic patients suggest that this substance may be responsible for reaching the threshold needed for PE to develop as a maternal manifestation of ischemic placental disease. The FGR is characterized by an elevated maternal sFlt-1/PlGF ratio, which boosts at the moment of indicated delivery due to fetal risk. We concluded that angiogenic imbalance is reflective of placental disease regardless of its clinical manifestation in the mother, and may be used as support for the diagnosis and prognosis of FGR.

Circulating Angiogenic Factor Levels in Hypertensive Disorders of Pregnancy

BACKGROUND: Among women with hypertensive disorders of pregnancy, biomarkers may stratify risk for developing preeclampsia with severe features (sPE). METHODS: Across 18 U.S. centers, we prospectively measured the ratio of serum soluble fms-like tyrosine kinase 1 (sFlt-1) to placental growth factor (PlGF) in pregnant women hospitalized between 23 and 35 weeks of gestation. The primary outcome was predicting sPE, and secondary outcomes included predicting adverse outcomes within 2 weeks. The prognostic performance of the sFlt-1:PlGF ratio was assessed by using a derivation/validation design. RESULTS: A total of 1014 pregnant women were evaluated; 299 were included in the derivation cohort and 715 in the validation cohort. In the derivation cohort, the median sFlt-1:PlGF ratio was 200 (interquartile range, 53 to 458) among women who developed sPE compared with 6 (interquartile range, 3 to 26) in those who did not (P<0.001). The discriminatory ratio of ≥40 was then tested in the validation cohort and yielded a 65% positive (95% confidence interval [CI], 59 to 71) and a 96% negative (95% CI, 93 to 98) predictive value for the primary outcome. The ratio performed better than standard clinical measures (area under the receiver-operating characteristic curve, 0.92 versus <0.75 for standard-of-care tests). Compared with women with a ratio <40, women with a ratio ≥40 were at higher risk for adverse maternal outcomes (16.1% versus 2.8%; relative risk, 5.8; 95% CI, 2.8 to 12.2). CONCLUSIONS: In women with a hypertensive disorder of pregnancy presenting between 23 and 35 weeks of gestation, measurement of serum sFlt-1:PlGF provided stratification of the risk of progressing to sPE within the coming fortnight. (Funded by Cedars-Sinai Medical Center and Thermo Fisher Scientific; ClinicalTrials.gov NCT03815110.)

Prediction of Adverse Outcomes in De Novo Hypertensive Disorders of Pregnancy: Development and Validation of Maternal and Neonatal Prognostic Models

Effectively identifying high-risk patients with de novo hypertensive disorder of pregnancy (HDP) is required to enable timely intervention and to reduce adverse maternal and perinatal outcomes. Electronic medical record of pregnant women with de novo HDP were extracted from a birth cohort in Beijing, China. The adverse outcomes included maternal and fetal morbidities, mortality, or any other adverse complications. A multitude of machine learning statistical methods were employed to develop two prediction models, one for maternal complications and the other for perinatal deteriorations. The maternal model using the random forest algorithm produced an AUC of 0.984 (95% CI (0.978, 0.991)). The strongest predictors variables selected by the model were platelet count, fetal head/abdominal circumference ratio, and gestational age at the diagnosis of de novo HDP; The perinatal model using the boosted tree algorithm yielded an AUC of 0.925 (95% CI (0.907, 0.945]). The strongest predictor variables chosen were gestational age at the diagnosis of de novo HDP, fetal femur length, and fetal head/abdominal circumference ratio. These prediction models can help identify de novo HDP patients at increased risk of complications who might need intense maternal or perinatal care.

Pregnancy-Associated Liver Diseases

The liver disorders unique to pregnancy include hyperemesis gravidarum, intrahepatic cholestasis of pregnancy, acute fatty liver of pregnancy, and preeclampsia-associated hepatic impairment, specifically hemolysis, elevated liver enzymes, and low platelet count syndrome (HELLP). Their importance lies in the significant maternal and fetal/neonatal morbidity and mortality. Expeditious diagnosis and clinical evaluation is critical to ensure timely, appropriate care and minimize risks to the pregnant woman and her fetus/baby. A multidisciplinary approach is essential, including midwives, maternal-fetal-medicine specialists, anesthetists, neonatologists, and hepatologists.

Clinical Application of a Multiparameter-Based Nomogram Model in Predicting Preeclampsia

Based on single-center data, the related predictive factors of preeclampsia (PE) were investigated, and a nomogram prediction model was established and validated. A retrospective collection of 93 PE patients admitted to our hospital from January 2019 to January 2021 were included in the PE group. In addition, non-PE pregnant women were selected for physical examination during the same period for matching, and 170 normal pregnant women who met the matching conditions were found as the normal pregnancy group. Clinical data of the selected candidates were collected. The risk factors of PE were screened by logistic regression analysis, and the lipopograph prediction model was constructed and verified. Logistic analysis results showed that age (OR = 3.069, 95% CI = 1.233-7.638), prepregnancy BMI (OR = 2.896, 95% CI = 1.193-7.029), vitamin E deficiency (OR = 2.803, 95% CI = 1.134-6.928), 25-(OH)D (OR = 0.944, 95% CI = 0.903∼9.988), PLGF (OR = 0.887, 95% CI = 0.851∼0.924), PAPP-A (OR = 1.240, 95% CI = 1.131∼1.360), and PI (OR = 6.376, 95% CI = 1.163∼34.967) were the independent risk factors for PE prediction (P < 0.05). The ROC curve showed that the AUC of the model for predicting the risk of PE was 0.957 (95% CI: 0.935-0.979), and the specificity and sensitivity were 0.912 and 0.892, respectively. H-L goodness of the fit test showed that there was no statistical significance in the deviation between the actual observed value and the predicted value of the risk in the line graph model (χ 2 = 7.001, P=0.536). The bootstrap test was used for internal verification, and the original data were repeatedly sampled 1000 times. The average absolute error of the calibration curve is 0.014, and the fitting degree between the calibration curve and the ideal curve is good. Age, prepregnancy BMI, lack of vitamin E, 25-(OH)D, PLGF, PAPP-A, and PI are independent risk factors for predicting PE. The establishment of a nomogram prediction model based on the above parameters can help identify PE high-risk groups in the early clinical stage and provide a reference for individualized clinical diagnosis and treatment.

Ophthalmic artery peak systolic velocity ratio distinguishes preeclampsia from chronic and gestational hypertension: A prospective cohort study

OBJECTIVE

To examine whether the ophthalmic artery peak systolic velocity ratio (OA PSV-ratio) is higher in women with preeclampsia (PE), compared to gestational hypertension (GH) and chronic hypertension (CH), after controlling for confounding variables.

DESIGN

Prospective cohort.

SETTING

Specialist hypertension clinic in a tertiary referral centre.

POPULATION

Singleton pregnancies presenting between 32+0 to 36+6 weeks' gestation with PE (n=50), GH (n=54) and CH (n=56).

METHODS

Paired measurements of maternal mean arterial pressure (MAP) and OA PSV-ratio were performed by trained sonographers. Multiple linear regression was fitted to the OA PSV-ratio, including maternal characteristics and medical history, GH, PE and MAP and use of antihypertensive medication.

MAIN OUTCOME MEASURE

Whether PE is independently associated with higher OA PSV-ratio.

RESULTS

MAP was significantly higher in both GH (p=0.0015) and PE (p=0.008) than in CH pregnancies. There was no significant difference between PE and GH (0.670). The OA PSV-ratio was significantly higher in PE than CH (p=0.0008) and GH (p=0.015). There was no significant difference between the OA PSV-ratio in CH and GH (p=0.352). Multiple linear regression modelling showed that the OA PSV-ratio was influenced by maternal weight (p=0.005), maternal age (p=0.014), antihypertensive medications (p=0.007) and MAP (p<0.0001). After controlling for these variables, the OA PSV-ratio was still significantly higher in those with PE (p=0.0002).

CONCLUSIONS

The OA PSV-ratio is influenced by maternal weight, age, antihypertensive medications and MAP. PE is an independent predictor of OA PSV-ratio, which therefore may be a useful point-of-care test when assessing women presenting with hypertension.

Study protocol: establishment of a multicentre pre-eclampsia database and biobank in Sweden: GO PROVE and UP MOST, a prospective cohort study

INTRODUCTION

Pre-eclampsia, a multisystem disorder in pregnancy, is one of the most common causes of maternal morbidity and mortality worldwide. However, we lack methods for objective assessment of organ function in pre-eclampsia and predictors of organ impairment during and after pre-eclampsia. The women's and their partners' experiences of pre-eclampsia have not been studied in detail. To phenotype different subtypes of the disorder is of importance for prediction, prevention, surveillance, treatment and follow-up of pre-eclampsia.The aim of this study is to set up a multicentre database and biobank for pre-eclampsia in order to contribute to a safer and more individualised treatment and care.

METHODS AND ANALYSIS

This is a multicentre cohort study. Prospectively recruited pregnant women ≥18 years, diagnosed with pre-eclampsia presenting at Sahlgrenska University Hospital, Uppsala University Hospital and at Södra Älvsborgs Hospital, Sweden, as well as normotensive controls are eligible for participation. At inclusion and at 1-year follow-up, the participants donate biosamples that are stored in a biobank and they are also asked to participate in various organ-specific evaluations. In addition, questionnaires and interviews regarding the women's and partner's experiences are distributed at follow-up.

ETHICS AND DISSEMINATION

By creating a database and biobank, we will provide the means to explore the disorder in a broader sense and allow clinical and laboratory discoveries that can be translated to clinical trials aiming at improved care of women with pre-eclampsia. Further, to evaluate experiences and the psychological impact of being affected by pre-eclampsia can improve the care of pregnant women and their partners. In case of incidental pathological findings during examinations performed, they will be handled in accordance with clinical routine. Data are stored in a secure online database. Biobank samples are identified through the women's personal identification number and pseudonymised after identification in the biobank before analysis.This study was approved by the regional ethical review board in Gothenburg on 28 December 2018 (approval number 955-18) and by the Swedish Ethical Review Authority on 27 February 2019 (approval number 2019-00309).Results from the study will be published in international peer-reviewed journals.

TRIAL REGISTRATION NUMBER

ISRCTN13060768.

Development and external validation of a model for predicting adverse outcomes in women with preeclampsia: A retrospective study from two trans-regional centers in China

OBJECTIVES

Preeclampsia is a common complication of pregnancy that causes health problems for both the mother and her fetus. This study aimed to develop and externally validate a model to predict adverse outcomes in preeclampsia in a trans-regional two-center retrospective cohort of Chinese women.

STUDY DESIGN

To generate a model for the risk of women with adverse outcomes, we incorporated candidate variables in the development set in univariate, least absolute shrinkage and selection operator analysis and multivariable logistic regression. The performance of the model was evaluated for the receiver operating characteristic (ROC) curve, calibration and decision curve analysis. Further, we externally validated the model in an independent dataset.

MAIN OUTCOME MEASURES

Composite adverse outcomes within 48 h of admission.

RESULTS

There were 1 783 and 116 preeclampsia women in the development and validation set, respectively. The model included 10 predictors: gestational age at admission, irregular prenatal care, number of symptoms, mean arterial pressure, hematocrit, platelet count, fibrinogen, albumin, total bilirubin, and serum urea. The area under the ROC curve of the model was 0.867 in the development set and 0.841 in the external validation set. The calibration plots for the probability of adverse outcomes demonstrated a good correlation. Decision curve analysis further showed that our model had clinical application value. The nomogram and a software-based calculator (https://sdfyyfck.shinyapps.io/preeclampsia/) were constructed for convenient clinical use.

CONCLUSIONS

Such a model could be used as a useful tool for the assessment of hypertensive-related complications in Chinese preeclampsia patients.

Pre-eclampsia

Pre-eclampsia is a multisystem pregnancy disorder characterised by variable degrees of placental malperfusion, with release of soluble factors into the circulation. These factors cause maternal vascular endothelial injury, which leads to hypertension and multi-organ injury. The placental disease can cause fetal growth restriction and stillbirth. Pre-eclampsia is a major cause of maternal and perinatal mortality and morbidity, especially in low-income and middle-income countries. Prophylactic low-dose aspirin can reduce the risk of preterm pre-eclampsia, but once pre-eclampsia has been diagnosed there are no curative treatments except for delivery, and no drugs have been shown to influence disease progression. Timing of delivery is planned to optimise fetal and maternal outcomes. Clinical trials have reported diagnostic and prognostic strategies that could improve fetal and maternal outcomes and have evaluated the optimal timing of birth in women with late preterm pre-eclampsia. Ongoing studies are evaluating the efficacy, dose, and timing of aspirin and calcium to prevent pre-eclampsia and are evaluating other drugs to control hypertension or ameliorate disease progression.

External validation of clinical prediction models: simulation-based sample size calculations were more reliable than rules-of-thumb

INTRODUCTION

Sample size "rules-of-thumb" for external validation of clinical prediction models suggest at least 100 events and 100 non-events. Such blanket guidance is imprecise, and not specific to the model or validation setting. We investigate factors affecting precision of model performance estimates upon external validation, and propose a more tailored sample size approach.

METHODS

Simulation of logistic regression prediction models to investigate factors associated with precision of performance estimates. Then, explanation and illustration of a simulation-based approach to calculate the minimum sample size required to precisely estimate a model's calibration, discrimination and clinical utility.

RESULTS

Precision is affected by the model's linear predictor (LP) distribution, in addition to number of events and total sample size. Sample sizes of 100 (or even 200) events and non-events can give imprecise estimates, especially for calibration. The simulation-based calculation accounts for the LP distribution and (mis)calibration in the validation sample. Application identifies 2430 required participants (531 events) for external validation of a deep vein thrombosis diagnostic model.

CONCLUSION

Where researchers can anticipate the distribution of the model's LP (eg, based on development sample, or a pilot study), a simulation-based approach for calculating sample size for external validation offers more flexibility and reliability than rules-of-thumb.

Establishment and assessment of a nomogram for predicting adverse outcomes of preterm preeclampsia

Objective

This prospective study was designed to develop and internally validate an accurate prognostic nomogram model with which to predict the adverse outcomes of preterm preeclampsia.

Methods

Pregnant women with preeclampsia were divided into the adverse outcome group and the no adverse outcome group. The Kaplan–Meier method, univariate Cox regression analysis, and calculation of the concordance index (C-index) were applied to predictive evaluation of the nomogram. Calibration curves were drawn to test the nomogram prediction and actual observation of the adverse outcome rate.

Results

After 1000 internal validations of bootstrap resampling, the C-index of the nomogram for predicting adverse outcomes within 48 hours was 0.74 and the cut-off value was 0.53, with a sensitivity of 61.57% and a specificity of 76.93%. The C-index of the nomogram for predicting adverse outcomes within 7 days was 0.76 and the cut-off value was 0.37, with a sensitivity of 58.17% and a specificity of 84.82%. The calibration curves showed good concordance of incidence of adverse outcomes between nomogram prediction and actual observation.

Conclusion

Cox regression has certain guiding significance in preventing and treating adverse outcomes, choosing the time of termination of pregnancy, and improving the prognosis of the mother and child.

A prognostic model to guide decision-making on timing of delivery in late preterm pre-eclampsia: the PEACOCK prospective cohort study

BACKGROUND

Pre-eclampsia affects around 2-3% of all pregnancies, and is associated with potential serious complications for the woman and the baby. Once diagnosed, progression of the syndrome can be unpredictable, and decisions around timing of delivery need to take into account evolving maternal complications and perinatal morbidity. Novel prognostic models and blood biomarkers for determination of need for delivery in pregnancies with pre-eclampsia are now emerging.

OBJECTIVE

The objective of the study was to establish a prognostic model to inform optimal timing of delivery in women with late preterm pre-eclampsia (34^+ 0 to 36^+ 6 weeks' gestation), comparing novel candidate biomarkers (e.g. placental growth factor) with clinical and routinely collected blood/urinary parameters [incorporated into the PREP-S (Prediction models for Risk of Early-onset Pre-eclampsia - Survival) model] to determine clinically indicated need for delivery for pre-eclampsia (or related complications) within 7 days of assessment.

METHODS

Prospective recruitment of women in whom blood samples for placental growth factor and soluble fms-like tyrosine kinase-1 testing was obtained, alongside clinical data, for use within the PREP-S model. Candidate variables were compared using standard methods (sensitivity, specificity, receiver operator curve areas). Estimated probability of early delivery from PREP-S was compared with actual event rates by calibration.

SETTING

The PEACOCK (Prognostic indicators of severe disEAse in women with late preterm pre-eClampsia tO guide deCision maKing on timing of delivery) study was a prospective cohort study, nested within the PHOENIX (Pre-eclampsia in HOspital: Early iNductIon or eXpectant management) trial.

PARTICIPANTS

Women between 34^+ 0 and 36^+ 6 weeks' gestation, with a diagnosis of pre-eclampsia, in whom a plasma (ethylenediaminetetraacetic acid) blood sample for placental growth factor testing was obtained, alongside clinical data for the assessment of variables in a prognostic model.

MAIN OUTCOME MEASURES

Clinically indicated need for delivery for pre-eclampsia within 7 days of assessment. Statistical analysis: both PREP-S and placental growth factor were assessed and compared using standard methods (sensitivity and specificity for placental growth factor thresholds of 100 pg/ml and < 12 pg/ml, and receiver operating characteristic areas for continuous measurements). The estimated probability of early delivery from PREP-S was compared with actual event rates for women with similar probabilities by calibration. Calibration using logistic regression was also used.

RESULTS

Between 27 April 2016 and 24 December 2018, 501 women were recruited to the study. Although placental growth factor testing had high sensitivity (97.9%) for delivery within 7 days, the negative predictive value was only 71.4% and the specificity was low (8.4%). The area under the curve for the clinical prediction model (PREP-S) and placental growth factor in this cohort in determining need for delivery within 7 days was 0.64 (standard error 0.03) and 0.60 (standard error 0.03), respectively, and 0.65 (standard error 0.03) in combination.

LIMITATIONS

A high proportion of women in this cohort already had low placental growth factor concentrations at the time of confirmed diagnosis, which reduced the ability of the biomarker to further predict adverse outcomes.

CONCLUSIONS

In this group of women with late preterm pre-eclampsia, placental growth factor measurement is not likely to add to the current clinical assessment to help plan care for late preterm pre-eclampsia regarding timing of delivery. Existing models developed in women with early-onset pre-eclampsia to predict complications cannot be used to predict clinically indicated need for delivery in women with late preterm pre-eclampsia.

FUTURE WORK

Further statistical modelling and subgroup analysis is being considered to assess if improved model performance in the whole cohort or a subgroup can be achieved. Addition of other biomarkers to the model may also be of use and will be explored.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN01879376.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 30. See the NIHR Journals Library website for further project information.

Maternal medicine in the COVID era

The coronavirus disease-19 (COVID-19) pandemic has directly and indirectly impacted pregnant women with co-morbidities or antenatal medical complications, through vulnerability to the severe effects of COVID-19 and service reconfiguration. Women with diabetes or hypertension in pregnancy are at higher risk of admission to intensive care, need for invasive ventilation and death from COVID-19. Suggested service modifications specific to maternal medicine services include home measurement of blood glucose or blood pressure, the use of risk calculators, adaptations to screening criteria for gestational diabetes and monitoring of obstetric cholestasis. Neither the added risk of COVID-19 on pregnant women with medical comorbidities nor the impact of maternal medicine service modifications has yet been established.

Prognostic indicators of severe disease in late preterm pre-eclampsia to guide decision making on timing of delivery: The PEACOCK study

OBJECTIVE

To assess the diagnostic performance of angiogenic biomarkers in determining need for delivery in seven days in women with late preterm preeclampsia.

STUDY DESIGN

In a prospective observational cohort study in 36 maternity units across England and Wales, we studied the diagnostic accuracy of placental growth factor (PlGF) and sFlt-1 in determining the risk of complications requiring delivery in late preterm (34⁺⁰ to 36⁺⁶ weeks' gestation) preeclampsia. Angiogenic biomarkers were measured using the Quidel (PlGF) and Roche (sFlt-1:PlGF ratio) assays. Additional clinical data was obtained for use within the established 'Prediction of complications in early-onset pre-eclampsia' (PREP)-S prognostic model. Biomarkers were assessed using standard methods (sensitivity, specificity, Receiver Operator Curve areas). Estimated probability of early delivery from PREP-S was compared to actual event rates.

MAIN OUTCOME MEASURES

Clinically indicated need for delivery for pre-eclampsia within seven days.

RESULTS

PlGF (Quidel) testing had high sensitivity (97.9%) for delivery within seven days, but negative predictive value was only 71.4%, with low specificity (8.4%), with similar results from sFlt-1/PlGF assay. The area under the curve for PlGF was 0.60 (SE 0.03), and 0.65 (0.03), and 0.64 (0.03) for PREP-S in combination with PlGF, and sFlt-1:PlGF, respectively.

CONCLUSIONS

Angiogenic biomarkers do not add to clinical assessment to help determine need for delivery for women with late preterm pre-eclampsia. Existing models developed in women with early-onset pre-eclampsia to predict complications cannot be used to predict clinically indicated need for delivery in women with late preterm pre-eclampsia.

The impact of the definition of preeclampsia on disease diagnosis and outcomes: a retrospective cohort study

BACKGROUND

The diagnostic criteria for preeclampsia have evolved from the traditional definition of de novo hypertension and proteinuria to a broader definition of hypertension with evidence of end-organ dysfunction. Although this change is endorsed by various societies such as the International Society for the Study of Hypertension in Pregnancy and the American College of Obstetricians and Gynecologists, there remains controversy with regard to the implementation of broader definitions and the most appropriate definition of end-organ dysfunction.

OBJECTIVE

This study aimed to assess the impact of different diagnostic criteria for preeclampsia on rates of disease diagnosis, disease severity, and adverse outcomes and to identify associations between each component of the different diagnostic criteria and adverse pregnancy outcomes.

STUDY DESIGN

We performed a retrospective cohort study of singleton pregnancies at Monash Health between January 1, 2016 and July 31, 2018. Within this population, all cases of gestational hypertension and preeclampsia were reclassified according to the International Society for the Study of Hypertension in Pregnancy 2001, American College of Obstetricians and Gynecologists 2018, and International Society for the Study of Hypertension in Pregnancy 2018 criteria. Differences in incidence of preeclampsia and maternal and perinatal outcomes were compared between the International Society for the Study of Hypertension in Pregnancy 2001 group and the extra cases identified by American College of Obstetricians and Gynecologists 2018 and International Society for the Study of Hypertension in Pregnancy 2018. Outcomes assessed included biochemical markers of preeclampsia, a composite of adverse maternal outcomes, and a composite of adverse perinatal outcomes. Multiple logistic regression analysis was also performed to assess each component of the American College of Obstetricians and Gynecologists 2018 and International Society for the Study of Hypertension in Pregnancy 2018 criteria and their associations with adverse maternal and perinatal outcomes.

RESULTS

Of 22,094 pregnancies, 751 (3.4%) women had preeclampsia as defined by any of the 3 criteria. Compared with International Society for the Study of Hypertension in Pregnancy 2001, the American College of Obstetricians and Gynecologists 2018 criteria identified an extra 42 women (n=654 vs n=696, 6.4% relative increase) with preeclampsia, and International Society for the Study of Hypertension in Pregnancy 2018 identified an extra 97 women (n=654 vs n=751, 14.8% relative increase). The additional women identified by International Society for the Study of Hypertension in Pregnancy 2018 exhibited a milder form of disease with lower rates of severe hypertension (62.4% vs 44.3%; P<.01) and magnesium sulfate use (11.9% vs 4.1%; P<.05) and a trend toward lower rates of adverse maternal outcomes (9.8% vs 4.1%). These women also delivered at a later gestation, and their babies had a lower number of neonatal intensive care unit admissions and adverse perinatal outcomes. Objective features such as fetal growth restriction, thrombocytopenia, renal and liver impairment, and proteinuria were associated with an increased risk of adverse maternal and perinatal outcomes, whereas subjective neurologic features demonstrated poorer associations.

CONCLUSION

Implementation of broader definitions of preeclampsia will result in an increased incidence of disease diagnosis. However, because women who exclusively fulfill the new criteria have a milder phenotype of the disease, it remains uncertain whether this will translate to improved outcomes.

Development and validation of a prediction model on severe maternal outcomes among pregnant women with pre-eclampsia: a 10-year cohort study

Pre-eclampsia is a severe hypertensive disorder of pregnancy and could lead to severe maternal morbidities and death. Our study aimed to develop and validate a prognostic prediction model for severe maternal outcomes among Chinese population with pre-eclampsia. We conducted a 10-year cohort study in a referral center by collecting all pregnant women who diagnosed as pre-eclampsia and delivered from 2005 to 2014. A composite of severe maternal outcomes, including maternal near-miss defined by World Health Organization, cortical blindness/retinal detachment, temporary facial paralysis and maternal death, were adopted. We used logistic regression model to develop Model 1 by retaining the predictors of p < 0.05, and further conducted Model 2 by adding quadratic terms and interaction terms to Model 1. We undertook a bootstrapping validation and estimated the model performance. A total of 397 pregnant women suffered from severe maternal outcomes among 2,793 eligible participants, with an incidence of 14.21% (95% confidence interval (CI) 12.91%–15.51%). Of 13 predictors were finally selected in Model 1. Combined with quadratic and interactive terms, the Model 2 showed higher area under the ROC curve (82.2%, 95% CI 79.6%–84.7%) and good calibration. By the bootstrapping validation, similar model performances were present.

Added prognostic value of longitudinal changes of angiogenic factors in early-onset severe pre-eclampsia: a prospective cohort study

OBJECTIVE

To assess in women with early-onset severe pre-eclampsia whether longitudinal changes in angiogenic factors improve the prediction of adverse outcome.

DESIGN

Prospective cohort study.

SETTING

Maternity units in two Spanish hospitals.

POPULATION

Women with diagnosis of early-onset severe pre-eclampsia.

METHODS

Levels of placental growth factor (PlGF), soluble fms-like tyrosine kinase (sFlt-) and sFlt-1/PlGF ratio were measured at admission and before delivery, and average daily change calculated. The association of longitudinal changes of angiogenic factors with the time interval to delivery and with complications was evaluated by logistic and Cox regression.

MAIN OUTCOME MEASURES

Interval to delivery and composite of adverse outcomes.

RESULTS

We included 63 women, of which 26 (41.3%) had a complication. Longitudinal changes of sFlt-1 were more pronounced in complicated pregnancies (median: 1047 versus 342 pg/ml/day; P = 0.04). On the multivariate analysis, the clinical risk score and sFlt-1 at admission explained 6.2% of the uncertainty for complication; the addition of sFlt-1 longitudinal changes improved this to 25.3% (P = 0.002). The median time from admission to delivery was 4 days (95% CI 1.6-6.04) in those in the highest quartile of sFlt-1 longitudinal changes versus 16 days (95% CI 12.4-19.6) in the remaining women (Log-rank test P < 0.001).

CONCLUSIONS

Longitudinal changes in sFlt-1 maternal levels from admission for confirmed early-onset severe pre-eclampsia add to baseline characteristics in the prediction of adverse outcome and interval to delivery.

TWEETABLE ABSTRACT

In early-onset severe pre-eclampsia, longitudinal changes in sFlt-1 levels improve the prediction of complications and interval to delivery.

Transparent Reporting of Multivariable Prediction Models in Journal and Conference Abstracts: TRIPOD for Abstracts

Clear and informative reporting in titles and abstracts is essential to help readers and reviewers identify potentially relevant studies and decide whether to read the full text. Although the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) statement provides general recommendations for reporting titles and abstracts, more detailed guidance seems to be desirable. The authors present TRIPOD for Abstracts, a checklist and corresponding guidance for reporting prediction model studies in abstracts. A list of 32 potentially relevant items was the starting point for a modified Delphi procedure involving 110 experts, of whom 71 (65%) participated in the web-based survey. After 2 Delphi rounds, the experts agreed on 21 items as being essential to report in abstracts of prediction model studies. This number was reduced by merging some of the items. In a third round, participants provided feedback on a draft version of TRIPOD for Abstracts. The final checklist contains 12 items and applies to journal and conference abstracts that describe the development or external validation of a diagnostic or prognostic prediction model, or the added value of predictors to an existing model, regardless of the clinical domain or statistical approach used.

Statistical risk prediction models for adverse maternal and neonatal outcomes in severe preeclampsia in a low-resource setting: proposal for a single-centre cross-sectional study at Mpilo Central Hospital, Bulawayo, Zimbabwe

Hypertensive disorders in pregnancy are a leading cause of maternal and perinatal morbidity and mortality, especially in low-resource settings. Identifying mothers and babies at greatest risk of complications would enable intervention to be targeted to those most likely to benefit from them. However, current risk prediction models have a wide range of sensitivity (42-81%) and specificity (87-92%) indicating that improvements are needed. Furthermore, no predictive models have been developed or evaluated in Zimbabwe. This proposal describes a single centre retrospective cross-sectional study which will address the need to further develop and test statistical risk prediction models for adverse maternal and neonatal outcomes in low-resource settings; this will be the first such research to be carried out in Zimbabwe. Data will be collected on maternal demographics characteristics, outcome of prior pregnancies, past medical history, symptoms and signs on admission, results of biochemical and haematological investigations. Adverse outcome will be defined as a composite of maternal morbidity and mortality and perinatal morbidity and mortality. Association between variables and outcomes will be explored using multivariable logistic regression. Critically, new risk prediction models introduced for our clinical setting may reduce avoidable maternal and neonatal morbidity and mortality at local, national, regional and international level.

The use of rigorous methods was strongly warranted among prognostic prediction models for obstetric care

OBJECTIVE

The objective of the study was to examine methodological characteristics about the design and conduct in prognostic prediction models used for obstetric care.

STUDY DESIGN AND SETTING

We searched PubMed for studies on prognostic prediction models for obstetric care, published in top general medicine or major specialty journals between January 2011 and February 2018. Teams of method-trained investigators independently screened titles and abstracts and collected data using a prespecified, pilot-tested, structured questionnaire.

RESULTS

In total, 91 studies were eligible, of which two were published in top general medicine journals, 20 (22.0%) involved an epidemiologist or statistician, 18 (19.4%) published study protocols, 53 (58.2%) did not include any model validation, 20 (22.0%) did not clearly state the intended timing of use, 23 (25.3%) had no eligibility criteria, 15 (16.5%) did not use clear criteria for ascertaining outcome, and 69 (75.82%) did not apply blinding to outcome assessment. Among those models, 11 (12.1%) included participants fewer than 200 events, 41 (48.8%) had fewer than 100 events, and 19 (24.7%) had fewer than 10 events per variable.

CONCLUSION

The prognostic prediction models have important limitations in design and conduct. Substantial efforts are needed to strengthen the production of reliable prognostic prediction models for obstetric care.

Thresholds for Ambulatory Blood Pressure Monitoring Based on Maternal and Neonatal Outcomes in Late Pregnancy in a Southern Chinese Population

Background

In contrast to the general population, outcome‐derived thresholds for diagnosing ambulatory hypertension in pregnancy are not yet available. We aimed to identify and compare outcome‐derived ambulatory blood pressure (BP) monitoring thresholds for adverse perinatal outcomes by using approaches related and not related to clinic BP in a southern Chinese population.

Methods and Results

Ambulatory BP monitoring was performed in a cohort of 1768 high‐risk participants in late pregnancy who were not taking antihypertensive medications. Participants were followed for composite maternal (severe complications) and neonatal (pregnancy loss, advanced neonatal care, and small for gestational age) outcomes. Modeling of clinic BP–unrelated approaches revealed a nonlinear threshold effect of ambulatory diastolic BP on the composite outcome, with increased risk for daytime ≥79 mm Hg and 24‐hour measurement ≥76 mm Hg. For other ambulatory BP components showing linear associations with outcome, the following thresholds were identified: 131 mm Hg for daytime systolic, 121 mm Hg for nighttime systolic, 130 mm Hg for 24‐hour systolic, and 73 mm Hg for night‐time diastolic BP. These thresholds unrelated to clinic BP were lower than the equivalents yielding a similar probability of outcome to clinic BP of 140/90 mm Hg and were comparable with equivalents to clinic BP of 130/80 mm Hg.

Conclusions

Using an outcome‐derived approach unrelated to clinic BP, we identified rounded thresholds to define ambulatory hypertension in at‐risk women in late pregnancy in a southern Chinese population as follows: 130/80 mm Hg for daytime, 120/75 mm Hg for nighttime, and 130/75 mm Hg for 24‐hour measurement. For wider clinical applicability and to align both nonpregnancy and pregnancy ambulatory BP monitoring with an outcomes‐based approach, prospective, multiethnic, international studies from early pregnancy onward will be required.

Blood-based cerebral biomarkers in preeclampsia: Plasma concentrations of NfL, tau, S100B and NSE during pregnancy in women who later develop preeclampsia - A nested case control study

Objective

To evaluate if concentrations of the neuronal proteins neurofilament light chain and tau are changed in women developing preeclampsia and to evaluate the ability of a combination of neurofilament light chain, tau, S100B and neuron specific enolase in identifying neurologic impairment before diagnosis of preeclampsia.

Methods

A nested case-control study within a longitudinal study cohort was performed. 469 healthy pregnant women were enrolled between 2004–2007 and plasma samples were collected at gestational weeks 10, 25, 28, 33 and 37. Plasma concentrations of tau and neurofilament light chain were analyzed in 16 women who eventually developed preeclampsia and 36 controls throughout pregnancy with single molecule array (Simoa) method and compared within and between groups. S100B and NSE had been analyzed previously in the same study population. A statistical model with receiving characteristic operation curve was constructed with the four biomarkers combined.

Results

Plasma concentrations of neurofilament light chain were significantly increased in women who developed preeclampsia in gestational week 33 (11.85 ng/L, IQR 7.48–39.93 vs 6.80 ng/L, IQR 5.65–11.40) and 37 (22.15 ng/L, IQR 10.93–35.30 vs 8.40 ng/L, IQR 6.40–14.30) and for tau in gestational week 37 (4.33 ng/L, IQR 3.97–12.83 vs 3.77 ng/L, IQR 1.91–5.25) in contrast to healthy controls. A combined model for preeclampsia with tau, neurofilament light chain, S100B and neuron specific enolase in gestational week 25 displayed an area under the curve of 0.77, in week 28 it was 0.75, in week 33 it was 0.89 and in week 37 it was 0.83. Median week for diagnosis of preeclampsia was at 38 weeks of gestation.

Conclusion

Concentrations of both tau and neurofilament light chain are increased in the end of pregnancy in women developing preeclampsia in contrast to healthy pregnancies. Cerebral biomarkers might reflect cerebral involvement before onset of disease.

Large-scale external validation and comparison of prognostic models: an application to chronic obstructive pulmonary disease

BACKGROUND

External validations and comparisons of prognostic models or scores are a prerequisite for their use in routine clinical care but are lacking in most medical fields including chronic obstructive pulmonary disease (COPD). Our aim was to externally validate and concurrently compare prognostic scores for 3-year all-cause mortality in mostly multimorbid patients with COPD.

METHODS

We relied on 24 cohort studies of the COPD Cohorts Collaborative International Assessment consortium, corresponding to primary, secondary, and tertiary care in Europe, the Americas, and Japan. These studies include globally 15,762 patients with COPD (1871 deaths and 42,203 person years of follow-up). We used network meta-analysis adapted to multiple score comparison (MSC), following a frequentist two-stage approach; thus, we were able to compare all scores in a single analytical framework accounting for correlations among scores within cohorts. We assessed transitivity, heterogeneity, and inconsistency and provided a performance ranking of the prognostic scores.

RESULTS

Depending on data availability, between two and nine prognostic scores could be calculated for each cohort. The BODE score (body mass index, airflow obstruction, dyspnea, and exercise capacity) had a median area under the curve (AUC) of 0.679 [1st quartile-3rd quartile = 0.655-0.733] across cohorts. The ADO score (age, dyspnea, and airflow obstruction) showed the best performance for predicting mortality (difference AUCADO - AUCBODE = 0.015 [95% confidence interval (CI) = -0.002 to 0.032]; p = 0.08) followed by the updated BODE (AUCBODE updated - AUCBODE = 0.008 [95% CI = -0.005 to +0.022]; p = 0.23). The assumption of transitivity was not violated. Heterogeneity across direct comparisons was small, and we did not identify any local or global inconsistency.

CONCLUSIONS

Our analyses showed best discriminatory performance for the ADO and updated BODE scores in patients with COPD. A limitation to be addressed in future studies is the extension of MSC network meta-analysis to measures of calibration. MSC network meta-analysis can be applied to prognostic scores in any medical field to identify the best scores, possibly paving the way for stratified medicine, public health, and research.

Assessment of the fullPIERS Risk Prediction Model in Women With Early-Onset Preeclampsia

Supplemental Digital Content is available in the text.

Early-onset preeclampsia is associated with severe maternal and perinatal complications. The fullPIERS model (Preeclampsia Integrated Estimate of Risk) showed both internal and external validities for predicting adverse maternal outcomes within 48 hours for women admitted with preeclampsia at any gestational age. This ability to recognize women at the highest risk of complications earlier could aid in preventing these adverse outcomes through improved management. Because the majority (≈70%) of the women in the model development had late-onset preeclampsia, we assessed the performance of the fullPIERS model in women with early-onset preeclampsia to determine whether it will be useful in this subgroup of women with preeclampsia. Three cohorts of women admitted with early-onset preeclampsia between 2012 and 2016, from tertiary hospitals in Canada, the Netherlands, and United Kingdom, were used. Using the published model equation, the probability of experiencing an adverse maternal outcome was calculated for each woman, and model performance was evaluated based on discrimination, calibration, and stratification. The total data set included 1388 women, with an adverse maternal outcome rate of 7.3% within 48 hours of admission. The model had good discrimination, with an area under the receiver operating characteristic curve of 0.80 (95% confidence interval, 0.75–0.86), and a calibration slope of 0.68. The estimated likelihood ratio at the predicted probability of ≥30% was 23.4 (95% confidence interval, 14.83–36.79), suggesting a strong evidence to rule in adverse maternal outcomes. The fullPIERS model will aid in identifying women admitted with early-onset preeclampsia in similar settings who are at the highest risk of adverse outcomes, thereby allowing timely and effective interventions.

Development and validation of Prediction models for Risks of complications in Early-onset Pre-eclampsia (PREP): a prospective cohort study

BACKGROUND

The prognosis of early-onset pre-eclampsia (before 34 weeks' gestation) is variable. Accurate prediction of complications is required to plan appropriate management in high-risk women.

OBJECTIVE

To develop and validate prediction models for outcomes in early-onset pre-eclampsia.

DESIGN

Prospective cohort for model development, with validation in two external data sets.

SETTING

Model development: 53 obstetric units in the UK. Model transportability: PIERS (Pre-eclampsia Integrated Estimate of RiSk for mothers) and PETRA (Pre-Eclampsia TRial Amsterdam) studies.

PARTICIPANTS

Pregnant women with early-onset pre-eclampsia.

SAMPLE SIZE

Nine hundred and forty-six women in the model development data set and 850 women (634 in PIERS, 216 in PETRA) in the transportability (external validation) data sets.

PREDICTORS

The predictors were identified from systematic reviews of tests to predict complications in pre-eclampsia and were prioritised by Delphi survey.

MAIN OUTCOME MEASURES

The primary outcome was the composite of adverse maternal outcomes established using Delphi surveys. The secondary outcome was the composite of fetal and neonatal complications.

ANALYSIS

We developed two prediction models: a logistic regression model (PREP-L) to assess the overall risk of any maternal outcome until postnatal discharge and a survival analysis model (PREP-S) to obtain individual risk estimates at daily intervals from diagnosis until 34 weeks. Shrinkage was used to adjust for overoptimism of predictor effects. For internal validation (of the full models in the development data) and external validation (of the reduced models in the transportability data), we computed the ability of the models to discriminate between those with and without poor outcomes (c-statistic), and the agreement between predicted and observed risk (calibration slope).

RESULTS

The PREP-L model included maternal age, gestational age at diagnosis, medical history, systolic blood pressure, urine protein-to-creatinine ratio, platelet count, serum urea concentration, oxygen saturation, baseline treatment with antihypertensive drugs and administration of magnesium sulphate. The PREP-S model additionally included exaggerated tendon reflexes and serum alanine aminotransaminase and creatinine concentration. Both models showed good discrimination for maternal complications, with anoptimism-adjusted c-statistic of 0.82 [95% confidence interval (CI) 0.80 to 0.84] for PREP-L and 0.75 (95% CI 0.73 to 0.78) for the PREP-S model in the internal validation. External validation of the reduced PREP-L model showed good performance with a c-statistic of 0.81 (95% CI 0.77 to 0.85) in PIERS and 0.75 (95% CI 0.64 to 0.86) in PETRA cohorts for maternal complications, and calibrated well with slopes of 0.93 (95% CI 0.72 to 1.10) and 0.90 (95% CI 0.48 to 1.32), respectively. In the PIERS data set, the reduced PREP-S model had a c-statistic of 0.71 (95% CI 0.67 to 0.75) and a calibration slope of 0.67 (95% CI 0.56 to 0.79). Low gestational age at diagnosis, high urine protein-to-creatinine ratio, increased serum urea concentration, treatment with antihypertensive drugs, magnesium sulphate, abnormal uterine artery Doppler scan findings and estimated fetal weight below the 10th centile were associated with fetal complications.

CONCLUSIONS

The PREP-L model provided individualised risk estimates in early-onset pre-eclampsia to plan management of high- or low-risk individuals. The PREP-S model has the potential to be used as a triage tool for risk assessment. The impacts of the model use on outcomes need further evaluation.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN40384046.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.