Performance of the fullPIERS model in predicting adverse maternal outcomes in pre-eclampsia using patient data from the PIERS (Pre-eclampsia Integrated Estimate of RiSk) cohort, collected on admission

Clinical maternal risk parameters for the occurrence of maternal and fetal complications during preeclampsia in Congolese women

Several studies have demonstrated that predicting complications of preeclampsia up to 48 h before their occurrence enhances clinical management. This predictive ability allows for rational approaches in dealing with groups at high risk of maternal-fetal complications.

OBJECTIVE

This study aims to identify the clinical parameters strongly associated with maternal-fetal complications during preeclampsia in Congolese pregnant women.

METHOD

A descriptive and analytical study was conducted in the provincial city of Kinshasa from July 2018 to December 2021. The study population consisted of pregnant women with preeclampsia in three maternity units in Kinshasa. Determinants of complications were assessed using univariate and multivariate logistic regression.

RESULTS

In univariate logistic regression models, obesity, a history of hypertension, severe hypertension, and SpO2 < 90 % were identified as determinants of maternal-fetal complications. Conversely, a history of preeclampsia, treatment with MgSO4, or a combination of AntiHTA and MgSO4 reduced the risk of complications. In the multivariate model, after adjusting for all significant variables in the univariate model, severe hypertension, obesity, and SpO2 < 90 % were identified as independent determinants of maternal-fetal complications. The risk of complication was multiplied by 5 for severe hypertension, by 4 for obesity, and by 2 for SpO2 < 90 %. However, treating women with MgSO4 or a combination of AntiHTA and MgSO4 reduced the risk of complications by a factor of 4 and 6, respectively.

CONCLUSION

The presence of symptoms is more useful in predicting complications of preeclampsia than their absence in ruling out adverse events.

Prediction of complications of pre-eclampsia using the fullPIERS high risk predictive model

OBJECTIVE

To determine the predicted probability percentage of complications in women with pre-eclampsia using the Pre-eclampsia Integrated Estimate of Risk (fullPIERS) model within the first 24 h after admission and assess the model's predictive value for complications of pre-eclampsia.

METHODS

This was a prospective cohort study in which the fullPIERS model was applied to 256 pregnant women with pre-eclampsia within the first 24 h after admission. These women were then followed for 48 h to 7 days for maternal and fetal complications. Reciever operating characteristics (ROC) curves were generated to assess the performance of the fullPIERS model for adverse outcomes of pre-eclampsia.

RESULTS

Of the 256 women enrolled in the study, 101 women (39.5%) developed maternal complications, 120 women (46.9%) developed fetal complications, and 159 women (62.1%) developed both. With an area under the ROC curve of 0.843 (95% confidence interval 0.789-0.897), the fullPIERS model had good discriminating ability to predict complications at any time point between 48 h and 7 days after admission. The sensitivity and specificity of the model at a ≥5.9% cut-off value for predicting adverse maternal outcomes were 60% and 97%, respectively; they were 44% and 96%, respectively, for predicting combined fetomaternal complications with a cut-off value of 4.9%.

CONCLUSIONS

The fullPIERS model performs reasonably well in predicting adverse maternal and fetal outcomes in women with pre-eclampsia.

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.

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.

The prognostic utility of soluble fms-like tyrosine kinase-1 (sFlt-1) and placental growth factor (PIGF) biomarkers for predicting preeclampsia: a secondary analysis of data from the INSPIRE trial

Objective

To compare the prognostic performance of biomarkers soluble fms-like tyrosine kinase-1 (sFlt-1), Placental Growth Factor (PIGF), and sFlt-1/PIGF ratio as continuous values or as a binary cut-off of 38 for predicting preeclampsia (PE) within 7 days.

Design

Secondary analysis of a randomised clinical trial.

Setting

Oxford University Hospitals, Oxford, United Kingdom (UK).

Population

Pregnant women between 24⁺⁰ to 37⁺⁰ weeks of gestation with a clinical suspicion of preeclampsia.

Main outcome

Onset of preeclampsia within 7 days of the initial biomarker test.

Methods

Logistic regression model for onset of preeclampsia using: (i) sFlt-1 (ii) PIGF, (iii) sFlt-1/PIGF ratio (continuous), and (iv) sFlt-1/PIGF ratio as a cut-off above or below 38.

Results

Of the total 370 women, 42 (11.3%) developed PE within 7 days of screening. Models with sFlt-1 and sFlt-1/PIGF ratio (continuous) had greater overall performance than models with PIGF or with sFlt-1/PIGF ratio as a cut-off at 38 (R²: sFlt-1 = 55%, PIGF = 38%, sFlt-1/PIGF ratio = 57%, sFlt-1/PIGF ratio as cut-off at 38 model = 46%). The discrimination performance was the highest in sFlt-1 and sFlt-1/PIGF ratio (continuous) (c-statistic, sFlt-1 = 0.94, sFlt-1/PIGF ratio (continuous) = 0.94) models compared to PIGF or sFlt-1/PIGF cut-off models (c-statistic, PIGF = 0.87, sFlt-1/PIGF cut-off = 0.89).

Conclusion

Models using continuous values of sFlt-1 only or sFlt-1/PIGF ratio had better predictive performance compared to a PIGF only or the model with sFlt-1/PIGF ratio as a cut-off at 38. Further studies based on a larger sample size are warranted to substantiate this finding.

Development and Internal Validation of a Risk Prediction Model for Acute Cardiovascular Morbidity in Preeclampsia

BACKGROUND

Persons with preeclampsia are at increased short-term risk of adverse cardiovascular outcomes during pregnancy and the early postpartum period. We aimed to develop and internally validate a risk assessment tool to predict acute cardiovascular morbidity in preeclampsia.

METHODS

The study was conducted at an academic obstetric hospital. Participants with preeclampsia at delivery between 2007 and 2017 were included. A model to predict acute cardiovascular morbidity at delivery and within 6 weeks postpartum was developed and evaluated. The primary composite outcome included pulmonary edema/acute heart failure, myocardial infarction, aneurysm, cardiac arrest/ventricular fibrillation, heart failure/arrest during surgery or procedure, cerebrovascular disorders, cardiogenic shock, conversion of cardiac rhythm, and difficult-to-control severe hypertension. We assessed model discrimination and calibration. We used bootstrapping for internal validation.

RESULTS

4,171 participants with preeclampsia were included. The final model comprised 8 variables. Predictors positively associated with acute cardiovascular morbidity (presented as odds ratio [OR] with 95% confidence interval [CI]) were: gestational age at delivery (20-36 weeks 5.36 [3.67, 7.82]; 37-38 weeks 1.75 [1.16, 2.64]), maternal age (≥40 years 1.65 [1.00, 2.72]; 35-39 years 1.49 [1.07, 2.09]), and prior cesarean delivery (1.47, [1.01, 2.13]). The model had an area under the receiver operating characteristic curve of 0.72 (95% CI [0.69, 0.74]). Moreover, it was adequately calibrated and performed well on internal validation.

CONCLUSIONS

This risk prediction tool identified women with preeclampsia at highest risk of acute cardiovascular morbidity. If externally validated, this tool may facilitate early interventions aimed at preventing adverse cardiovascular outcomes in pregnancy and postpartum.

Alternatives of Risk Prediction Models for Preeclampsia in a Low Middle-Income Setting

Abstract Objectives:  To  develop prediction models for the first-trimester prediction of PE (PE) using the established biomarkers including maternal characteristics and history, mean arterial pressure (MAP), uterine artery Doppler pulsatility index (UtA-PI ), and Placental Growth Factor (PlGF)) in combination with Ophthalmic artery Doppler peak ratio (PR). Methods:  This was a  prospective observational study in women attending a first-trimester screening at 11-14 weeks’  gestation. Maternal characteristics and history, measurement of MAP, ultrasound examination for UtA-PI measurement, maternal ophthalmic PR Doppler measurement, and serum  PlGF collection were performed during the visit. Logistic regression  analysis was used to determine if the maternal factor had a significant contribution in predicting PE. The Receiving Operator Curve (ROC) analysis was used to determine the area under the curve  (AUC), positive predictive value  (PPV), negative prefictive value (NPV) and positive screening cut-off in predicting the occurrence of PE at any gestational age.   Results: Of the 946 eligible participants, 71 (7,49%) subjects were affected by PE. Based on the ROC curves, optimal high-risk cutoff value for prediction of preeclampsia at any gestational age for model 2 (primary care model) in this Indonesia study population were 63% with the sensitivity and specificity of 71.8% and 71.2%, respectively. Both sensitivity and specificity for model 3 (complete model) were 70.4% and 74.9%, respectively for the cutoff value 58%. The area under the curve of model 2, model 3 was 0.7651 (95% CI: 0.7023-0.8279)) and 0.7911 (95% CI: 0.7312-0.8511), respectively, for predicting PE. In addition, PPV and NPV for model 2 were 16.8% and 96.9%, respectively. PPV and NPV for model 3 were 18.55 and 96.9%, respectively.   Conclusion: The prediction models of preeclampsia vary depending upon healthcare resource. Complete model is clinically superior to primary care model but it is not statistically significant.  Prognostic models should be easy to use, informative and low cost with great potential to improve maternal and neonatal health in Low Middle Income Country settings. 

Cardiovascular severe maternal morbidity in pregnant and postpartum women: development and internal validation of risk prediction models

OBJECTIVES

To develop and internally validate risk prediction models identifying women at risk for cardiovascular severe maternal morbidity (CSMM).

DESIGN

A retrospective cohort study.

SETTING

An obstetric teaching hospital between 2007 and 2017.

POPULATION

A total of 89 681 delivery hospitalisations.

METHODS

We created and evaluated two models, one predicting CSMM at delivery (delivery model) and the other predicting CSMM postpartum following discharge from delivery hospitalisation (postpartum CSMM). We assessed model discrimination and calibration and used bootstrapping for internal validation.

MAIN OUTCOME MEASURES

Cardiovascular severe maternal morbidity comprised the following confirmed conditions: pulmonary oedema/acute heart failure, myocardial infarction, aneurysm, cardiac arrest/ventricular fibrillation, heart failure/arrest during surgery or procedure, cerebrovascular disorders, cardiogenic shock, conversion of cardiac rhythm and difficult-to-control severe hypertension.

RESULTS

The delivery model contained 11 variables and 3 interaction terms. The strongest predictors were gestational hypertension, chronic hypertension, multiple gestation, cardiac lesions or valvular heart disease, maternal age ≥40 years and history of poor pregnancy outcome. The postpartum model comprised eight variables. The strongest predictors were severe pre-eclampsia, non-Hispanic Black race/ethnicity, chronic hypertension, gestational hypertension, non-severe pre-eclampsia and maternal age ≥40 years at delivery. The delivery and postpartum models had an area under the receiver operating characteristic curve of 0.87 (95% CI 0.85-0.89) and 0.85 (95% CI 0.80-0.90), respectively. Both models were adequately calibrated and performed well on internal validation.

CONCLUSIONS

These tools may help providers to identify women at highest risk of CSMM and enable future prevention measures.

TWEETABLE ABSTRACT

Risk assessment tools for cardiovascular severe maternal morbidity were developed and internally validated.

The PRECISE (PREgnancy Care Integrating translational Science, Everywhere) Network's first protocol: deep phenotyping in three sub-Saharan African countries

BACKGROUND

The PRECISE (PREgnancy Care Integrating translational Science, Everywhere) Network is a new and broadly-based group of research scientists and health advocates based in the UK, Africa and North America.

METHODS

This paper describes the protocol that underpins the clinical research activity of the Network, so that the investigators, and broader global health community, can have access to 'deep phenotyping' (social determinants of health, demographic and clinical parameters, placental biology and agnostic discovery biology) of women as they advance through pregnancy to the end of the puerperium, whether those pregnancies have normal outcomes or are complicated by one/more of the placental disorders of pregnancy (pregnancy hypertension, fetal growth restriction and stillbirth). Our clinical sites are in The Gambia (Farafenni), Kenya (Kilifi County), and Mozambique (Maputo Province). In each country, 50 non-pregnant women of reproductive age will be recruited each month for 1 year, to provide a final national sample size of 600; these women will provide culturally-, ethnically-, seasonally- and spatially-relevant control data with which to compare women with normal and complicated pregnancies. Between the three countries we will recruit ≈10,000 unselected pregnant women over 2 years. An estimated 1500 women will experience one/more placental complications over the same epoch. Importantly, as we will have accurate gestational age dating using the TraCer device, we will be able to discriminate between fetal growth restriction and preterm birth. Recruitment and follow-up will be primarily facility-based and will include women booking for antenatal care, subsequent visits in the third trimester, at time-of-disease, when relevant, during/immediately after birth and 6 weeks after birth.

CONCLUSIONS

To accelerate progress towards the women's and children's health-relevant Sustainable Development Goals, we need to understand how a variety of social, chronic disease, biomarker and pregnancy-specific determinants health interact to result in either a resilient or a compromised pregnancy for either mother or fetus/newborn, or both. This protocol has been designed to create such a depth of understanding. We are seeking funding to maintain the cohort to better understand the implications of pregnancy complications for both maternal and child health.

[External validation of FullPIERS model for prediction of adverse outcomes among women with pre-eclampsia in French maternity of 2014 to 2018]

OBJECTIVES

FullPIERS score (Pre-eclampsia Integrated Estimate of RiSk) is built in order to predict maternal outcomes among women with preeclampsia. Our objective is to assess external validity of this score among a population of French women.

METHODS

A retrospective study was conducted for all patients with pre-eclampsia (severe or not) admitted to a tertiary hospital center. A receiver operating characteristic (ROC) curve was constructed to determine accuracy of the model at 48 hours and 7 days after admittance and area under the curve (AUC) was calculated.

RESULTS

In total, 276 patients meet inclusions criterion. Among them, 217 were included and 61 (28 %) had one or more complication. Only 8 patients had two complications at two different moments (one at 48 hours and one at 7 days). The FullPiers score predicted maternels events at 48 hours with an area under the curve at 0.80 (IC95 % [0.74-0.85]). At 4.2 cut off, the sensitivity was 71 % and specifity 88 %. At 7 days, the area under the curve was 0.74 (IC95 % [0.67-0.79]), admiting a cutoff point for FullPIERS probability of 3.4, sensitivity was 59 % and specificity 85 %.

CONCLUSIONS

Our study show utility of FullPIERS score in french maternity. This model might be a useful tool for predicting complications in women with pre-eclampsia. Using of this score in clinical practice might help improving optimization of patient's care.

Association of plasma lactate concentration at admission of severe preeclampsia to maternal complications

OBJECTIVE

To evaluate in women with severe preeclampsia the association of lactate concentration at admission with maternal complications.

METHODS

A prospective cohort was created of women with severe preeclampsia consecutively admitted to an Obstetrical High-Dependency Unit. Plasma lactate concentration was measured at admission and its association to maternal complication was evaluated.

RESULTS

A total of 100 women were included, of which 30 (30%) had a maternal complication. The mean lactate plasma concentration in this group was significantly higher than in those uncomplicated cases (2.38 vs 3.1 mmol/L; p < 0.01). A total of 37 (37%) women had lactate concentrations at >3 mmol/L, which was associated to higher incidence of maternal complications (19% vs. 48.6%; p = 0.002; OR 4.03 [95% CI 1.64-9.9]). This association remained independent of other standard severity criteria (OR 3.89; 95%CI 1.22-12.4; p = 0.022).

CONCLUSION

Increased plasma lactate concentrations at admission in women with severe preeclampsia are independently associated to maternal complications.

Preeclampsia: Acute Complications and Management Priorities

Acute complications of preeclampsia contribute substantially to maternal and fetal morbidity and mortality. The considerable variation in onset, clinical presentation, and severity of this hypertensive disease that is unique to pregnancy creates challenges in identifying risk factors for clinical deterioration. Delivery of the fetus remains the only definitive treatment for preeclampsia. Surveillance of signs and symptoms and laboratory parameters consistent with progression in severity requires an appreciation of the dynamic and progressive nature of the disease. This article provides a comprehensive overview of the pathophysiology of preeclampsia, setting the foundation for discussion of management priorities for acute complications that pose the greatest risks to maternal health.

Risk factors for eclampsia in pregnant women with preeclampsia and positive neurosensory signs

Objective:

In Morocco, eclampsia remains the second major cause of maternal mortality. Conventionally, patients with preeclampsia and neurosensory signs (NSS) (e.g., headaches and hyperreflexia) are considered at high risk of worsening and progressing to eclampsia. However, this specific population is heterogeneous in terms of eclampsia occurrence. We aimed to identify the risk factors for the development of eclampsia in women with preeclampsia presenting with NSS at admission.

Materials and Methods:

We performed a single-center, retrospective case-control study of patients with preeclampsia with positive NSS from January 1^st, 2012 through December 31^st, 2015, to investigate predictive factors for eclamptic seizures. The case patients were pregnant women with severe preeclampsia who had NSS before developing eclampsia. Control subjects were those with positive NSS without the development of seizures during their hospital stay. One hundred-thirty eight patients with eclampsia and 272 control patients were enrolled.

Results:

Univariate analysis revealed that eclampsia was more likely to develop in patients with the following risk factors: maternal age ≤25 years (χ2=9.58, p=0.002), primiparity (χ2=6.38, p=0.011), inadequate prenatal care (χ2=11.62, p=0.001), systolic hypertension ≥160 mmHg (χ2=15.31, p<0.001), diastolic hypertension ≥110 mmHg (χ2=5.7, p=0.017), generalized acute edema (χ2=14.66, p<0.001), hematocrit <35% (χ2=11.16, p=0.001), serum creatinine >100 μmol/L (χ2=13.46, p<0.001), asparate aminotransferase (AST) >70 IU/L (χ2=10.15, p=0.001), and thrombocytopenia (χ2=22.73, p<0.001). Additionally, independent predictive factors for eclampsia in multivariate analysis included inadequate prenatal care [odds ratio (OR), 8.96 [95% confidence interval (CI): 3.9-20.5], p<0.001), systolic blood pressure ≥160 mmHg (OR, 3.130 [95% CI: 1.342-7.305], p=0.008), thrombocytopenia with a platelet count <50.000 (OR, 13.106 [95% CI: 1.344-127.823], p=0.027), AST ≥70 IU (OR, 3.575 [95% CI: 1.313-9.736], p=0.007), and elevated liver enzymes level, and low platelet count (ELLP) syndrome, which is an incomplete variant of HELLP syndrome (H for hemolysis) (OR, 5.83 [95% CI: 2.43- 13.9], p<0.001).

Conclusion:

This work highlights two major risk factors in this patient population, inadequate prenatal care and ELLP syndrome, which can help in the early identification of patients at highest risk of developing eclampsia and guide preventive measures.

Risk factors for adverse maternal and perinatal outcomes in women with preeclampsia: analysis of 1396 cases

Preeclampsia is a major cause of adverse maternal and perinatal outcomes, but how to identify women and fetuses at increased risk for later adverse events is a challenge. This study aimed to investigate the risk factors for adverse maternal and perinatal outcomes in women with preeclampsia. Data from 1396 women with preeclampsia were retrospectively collected and analyzed. Eighteen candidate risk factors and 12 adverse outcomes were investigated. The following factors were found to be significantly associated with at least one adverse outcome: maternal age 35 years or older, multiple birth, the usage of assisted reproductive technology, living in a rural area, history of pregnancy-induced hypertension, male fetus, multigravida, or having polycystic ovary syndrome, hemolysis, elevated liver enzymes, and low platelet count syndrome, intrahepatic cholestasis of pregnancy, cardiovascular disease, gestational diabetes mellitus, systemic lupus erythematosus, thyroid disease, or liver disease. Compared with patients without any identified risk factors, patients with preeclampsia with three or more risk factors were at increased risk for severe adverse outcomes. Those findings demonstrated that maternal risk factors could be used as indicators supplementary to clinical symptoms and laboratory test results for the risk assessment in women with preeclampsia.

Improved prediction of gestational hypertension by inclusion of placental growth factor and pregnancy associated plasma protein-a in a sample of Ghanaian women

BACKGROUND

We assessed whether adding the biomarkers Pregnancy Associated Plasma Protein-A (PAPP-A) and Placental Growth Factor (PlGF) to maternal clinical characteristics improved the prediction of a previously developed model for gestational hypertension in a cohort of Ghanaian pregnant women.

METHODS

This study was nested in a prospective cohort of 1010 pregnant women attending antenatal clinics in two public hospitals in Accra, Ghana. Pregnant women who were normotensive, at a gestational age at recruitment of between 8 and 13 weeks and provided a blood sample for biomarker analysis were eligible for inclusion. From serum, biomarkers PAPP-A and PlGF concentrations were measured by the AutoDELFIA immunoassay method and multiple of the median (MoM) values corrected for gestational age (PAPP-A and PlGF) and maternal weight (PAPP-A) were calculated. To obtain prediction models, these biomarkers were included with clinical predictors maternal weight, height, diastolic blood pressure, a previous history of gestational hypertension, history of hypertension in parents and parity in a logistic regression to obtain prediction models. The Area Under the Receiver Operating Characteristic Curve (AUC) was used to assess the predictive ability of the models.

RESULTS

Three hundred and seventy three women participated in this study. The area under the curve (AUC) of the model with only maternal clinical characteristics was 0.75 (0.64-0.86) and 0.89(0.73-1.00) for multiparous and primigravid women respectively. The AUCs after inclusion of both PAPP-A and PlGF were 0.82 (0.74-0.89) and 0.95 (0.87-1.00) for multiparous and primigravid women respectively.

CONCLUSION

Adding the biomarkers PAPP-A and PlGF to maternal characteristics to a prediction model for gestational hypertension in a cohort of Ghanaian pregnant women improved predictive ability. Further research using larger sample sizes in similar settings to validate these findings is recommended.

External Validation of the fullPIERS Model for Predicting Adverse Maternal Outcomes in Pregnancy Hypertension in Low- and Middle-Income Countries

The hypertensive disorders of pregnancy are leading causes of maternal mortality and morbidity, especially in low- and middle-income countries. Early identification of women with preeclampsia and other hypertensive disorders of pregnancy at high risk of complications will aid in reducing this health burden. The fullPIERS model (Preeclampsia Integrated Estimate of Risk) was developed for predicting adverse maternal outcomes from preeclampsia using data from tertiary centers in high-income countries and uses maternal demographics, signs, symptoms, and laboratory tests as predictors. We aimed to assess the validity of the fullPIERS model in women with the hypertensive disorders of pregnancy in low-resourced hospital settings. Using miniPIERS data collected on women admitted with hypertensive disorders of pregnancy between July 2008 and March 2012 in 7 hospitals in 5 low- and middle-income countries, the predicted probability of developing an adverse maternal outcome was calculated for each woman using the fullPIERS equation. Missing predictor values were imputed using multivariate imputation by chained equations. The performance of the model was evaluated for discrimination, calibration, and stratification capacity.

Among 757 women with complete predictor data (complete-case analyses), the fullPIERS model had a good area under the receiver-operating characteristic curve of 0.77 (95% confidence interval, 0.72–0.82) with poor calibration ( P <0·001 for the Hosmer–Lemeshow goodness-of-fit test). Performance as a rule-in tool was moderate (likelihood ratio: 5.9; 95% confidence interval, 4.23–8.35) for women with ≥30% predicted probability of an adverse outcome. The fullPIERS model may be used in low-resourced setting hospitals to identify women with hypertensive disorders of pregnancy at high risk of adverse maternal outcomes in need of immediate interventions.

Preventing deaths due to the hypertensive disorders of pregnancy

In this chapter, taking a life cycle and both civil society and medically oriented approach, we will discuss the contribution of the hypertensive disorders of pregnancy (HDPs) to maternal, perinatal and newborn mortality and morbidity. Here we review various interventions and approaches to preventing deaths due to HDPs and discuss effectiveness, resource needs and long-term sustainability of the different approaches. Societal approaches, addressing sustainable development goals (SDGs) 2.2 (malnutrition), 3.7 (access to sexual and reproductive care), 3.8 (universal health coverage) and 3c (health workforce strengthening), are required to achieve SDGs 3.1 (maternal survival), 3.2 (perinatal survival) and 3.4 (reduced impact of non-communicable diseases (NCDs)). Medical solutions require greater clarity around the classification of the HDPs, increased frequency of effective antenatal visits, mandatory responses to the HDPs when encountered, prompt provision of life-saving interventions and sustained surveillance for NCD risk for women with a history of the HDPs.

Prediction of Adverse Maternal Outcomes in Preeclampsia Using a Risk Prediction Model

BACKGROUND

This study was conducted to evaluate how the preeclampsia integrated estimate of risk (fullPIERS) model performs in the prediction of adverse maternal outcomes when the predictor variables are all obtained within 24-h of admission for preeclampsia.

METHODS

A prospective cohort study on 323 women who fulfilled definite inclusion and exclusion criteria was conducted. Subjects were monitored for clinical symptoms of preeclampsia, biochemical parameters, and adverse maternal and neonatal outcomes. A risk prediction score was calculated using the fullPIERS calculator. Statistical analysis of rates and ratios was carried out by assessing χ (2) test and odds ratio.

RESULTS

18.3 % (n = 60) had adverse maternal outcome and 42.8 % (n = 138) had adverse fetal outcome, and 43 (13.35 %) had combined adverse maternal and perinatal outcome. Dyspnea, visual disturbances, epigastric pain, and [Formula: see text] appeared to be highly significant risk factors. In the biochemical variables studied, serum creatinine and serum uric acid were found to have a significant association. The association between adverse perinatal outcome and vaginal delivery was highly significant (OR 0.35, 95 % CI 0.19, 0.63), and the P value was 0.0005. The likelihood ratio associated with the highest risk group (predicted probability of the outcome ≥30 %) showed excellent performance (i.e., 17.5) of fullPIERS model as a rule in test.

CONCLUSION

The fullPIERS model performed well in the prediction of adverse maternal outcomes in women with preeclampsia. It is easy to use. The model is based on the use of few important clinical and biochemical parameters and does not require extensive laboratory testing. Although it might be of limited use in a well-equipped tertiary care facility, this model can be utilized in the setting of district or sub-district level hospitals to identify patients who are at risk of complications due to preeclampsia. Timely referral to a higher center will help in reducing the morbidity and mortality associated with this condition.

Effectiveness and safety of 1 vs 4 h blood pressure profile with clinical and laboratory assessment for the exclusion of gestational hypertension and pre-eclampsia: a retrospective study in a university affiliated maternity hospital

OBJECTIVE

We asked whether 60 compared with 240 min observation is sufficiently informative and safe for pregnancy day assessment (PDAC) of suspected pre-eclampsia (PE).

DESIGN

A retrospective study of 209 pregnant women (475 PDAC assessments, 6 months) with routinely collected blood pressure (BP), symptom and laboratory information. We proposed a 60 min screening algorithm comprising: absence of symptoms, normal laboratory parameters and ≤1high-BP reading (systolic blood pressure, SBP 140 mm Hg or higher or diastolic blood pressure, DBP 90 mm Hg or higher). We also evaluated two less inclusive screening algorithms. We determined short-term outcomes (within 4 h): severe hypertension, proteinuric hypertension and pregnancy-induced hypertension, as well as long-term outcome: PE-related diagnoses up to the early puerperium. We assessed performance of alternate screening algorithms performance using 2×2 tables.

RESULTS

1 in 3 women met all screen negative criteria at 1 h. Their risk of hypertension requiring treatment in the next 3 h was 1.8% and of failing to diagnose proteinuric hypertensive PE at 4 h was 5.1%. If BP triggers were 5 mm Hg lower, 1 in 6 women would be screen-negative of whom 1.1% subsequently develops treatment-requiring hypertension and 4.5% demonstrate short-term proteinuric hypertension. We present sensitivity, specificity, negative and positive likelihood ratios for alternate screening algorithms.

CONCLUSIONS

We endorse further research into the safest screening test where women are considered for discharge after 60 min. Safety, patient and staff satisfaction should be assessed prospectively. Any screening test should be used in conjunction with good clinical care to minimise maternal and perinatal hazards of PE.

Moving beyond silos: How do we provide distributed personalized medicine to pregnant women everywhere at scale? Insights from PRE-EMPT

While we believe that pre-eclampsia matters-because it remains a leading cause of maternal and perinatal morbidity and mortality worldwide-we are convinced that the time has come to look beyond single clinical entities (e.g. pre-eclampsia, postpartum hemorrhage, obstetric sepsis) and to look for an integrated approach that will provide evidence-based personalized care to women wherever they encounter the health system. Accurate outcome prediction models are a powerful way to identify individuals at incrementally increased (and decreased) risks associated with a given condition. Integrating models with decision algorithms into mobile health (mHealth) applications could support community and first level facility healthcare providers to identify those women, fetuses, and newborns most at need of facility-based care, and to initiate lifesaving interventions in their communities prior to transportation. In our opinion, this offers the greatest opportunity to provide distributed individualized care at scale, and soon.

Pre-eclampsia part 2: prediction, prevention and management

An antiangiogenic state might constitute a terminal pathway for the multiple aetiologies of pre-eclampsia, especially those resulting from placental abnormalities. The levels of angiogenic and antiangiogenic proteins in maternal blood change prior to a diagnosis of pre-eclampsia, correlate with disease severity and have prognostic value in identifying women who will develop maternal and/or perinatal complications. Potential interventions exist to ameliorate the imbalance of angiogenesis and, hence, might provide opportunities to improve maternal and/or perinatal outcomes in pre-eclampsia. Current strategies for managing pre-eclampsia consist of controlling hypertension, preventing seizures and timely delivery of the fetus. Prediction of pre-eclampsia in the first trimester is of great interest, as early administration of aspirin might reduce the risk of pre-eclampsia, albeit modestly. Combinations of biomarkers typically predict pre-eclampsia better than single biomarkers; however, the encouraging initial results of biomarker studies require external validation in other populations before they can be used to facilitate intervention in patients identified as at increased risk. Angiogenic and antiangiogenic factors might also be useful in triage of symptomatic patients with suspected pre-eclampsia, differentiating pre-eclampsia from exacerbations of pre-existing medical conditions and performing risk assessment in asymptomatic women. This Review article discusses the performance of predictive and prognostic biomarkers for pre-eclampsia, current strategies for preventing and managing the condition and its long-term consequences.

Pre-eclampsia, eclampsia and adverse maternal and perinatal outcomes: a secondary analysis of the World Health Organization Multicountry Survey on Maternal and Newborn Health

OBJECTIVE

To assess the incidence of hypertensive disorders of pregnancy and related severe complications, identify other associated factors and compare maternal and perinatal outcomes in women with and without these conditions.

DESIGN

Secondary analysis of the World Health Organization Multicountry Survey on Maternal and Newborn Health (WHOMCS) database.

SETTING

Cross-sectional study implemented at 357 health facilities conducting 1000 or more deliveries annually in 29 countries from Africa, Asia, Latin America and the Middle East.

POPULATION

All women suffering from any hypertensive disorder during pregnancy, the intrapartum or early postpartum period in the participating hospitals during the study period.

METHODS

We calculated the proportion of the pre-specified outcomes in the study population and their distribution according to hypertensive disorders' severity. We estimated the association between them and maternal deaths, near-miss cases, and severe maternal complications using a multilevel logit model.

MAIN OUTCOME MEASURES

Hypertensive disorders of pregnancy. Potentially life-threatening conditions among maternal near-miss cases, maternal deaths and cases without severe maternal outcomes.

RESULTS

Overall, 8542 (2.73%) women suffered from hypertensive disorders. Incidences of pre-eclampsia, eclampsia and chronic hypertension were 2.16%, 0.28% and 0.29%, respectively. Maternal near-miss cases were eight times more frequent in women with pre-eclampsia, and increased to up to 60 times more frequent in women with eclampsia, when compared with women without these conditions.

CONCLUSIONS

The analysis of this large database provides estimates of the global distribution of the incidence of hypertensive disorders of pregnancy. The information on the most frequent complications related to pre-eclampsia and eclampsia could be of interest to inform policies for health systems organisation.