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Objective We assessed whether bariatric surgery before pregnancy lowers the risk of severe maternal morbidity to a level comparable to no obesity. Summary of background data Obesity is a risk factor for severe maternal morbidity, but the potential for bariatric surgery to reduce the risk has not been studied. Methods We analyzed a retrospective cohort of 2,412,075 deliveries between 1989 and 2019 in Quebec, Canada. The main exposure measures were bariatric surgery before pregnancy and obesity without bariatric surgery, compared with no obesity. The outcome was severe maternal morbidity, a composite of life-threatening pregnancy complications. We estimated risk ratios (RR) and 95% confidence intervals (CI) for the association between bariatric surgery and severe maternal morbidity, adjusted for maternal characteristics. Results A total of 2654 deliveries (0.1%) were in women who had bariatric surgery, and 70,041 (29.0 per 1000) were in women who had severe maternal morbidity. Risk of severe maternal morbidity was not significantly elevated for bariatric surgery (RR 1.20; 95% CI 0.98-1.46), but was greater for obesity compared with no obesity (RR 1.60; 95% CI 1.55-1.64). Bariatric surgery was not associated with morbidities such as severe preeclampsia, sepsis, and cardiac complications compared with no obesity, but obesity was associated with elevated risks of these and other severe morbidities. Bariatric surgery was associated, however, with intensive care unit admission, compared with no obesity. Conclusions Pregnant women with prior bariatric surgery have similar risks as nonobese women for most types of severe maternal morbidity, except for intensive care unit admission.

Objective To examine long-term risks of mortality after a pregnancy complicated by severe maternal morbidity. Methods We analyzed a longitudinal cohort of 1,229,306 women who delivered in the province of Quebec, Canada from 1989 through 2016. Severe maternal morbidity included conditions such as cerebrovascular accidents, acute renal failure, severe preeclampsia, and other life-threatening complications. The outcome was in-hospital mortality after the last pregnancy, categorized as postpartum (42 days or fewer after delivery) and long-term (43 days to 29 years after delivery). We estimated hazard ratios (HRs) ofr mortality with 95% CI for severe maternal morbidity compared with no severe morbidity, using Cox regression models adjusted for maternal characteristics. Results Severe maternal morbidity occurred in 2.9% of women. The mortality rate associated with severe maternal morbidity was 0.86 per 1,000 person-years compared with 0.41 per 1,000 person-years for no morbidity. Compared with no morbidity, severe maternal morbidity was associated with two times the rate of death any time after delivery (95% CI 1.81-2.20). Severe cardiac complications (HR 7.00, 85% CI 4.94-9.91), acute renal failure (HR 4.35, 95% CI 2.66-7.10), and cerebrovascular accidents (HR 4.03, 95% CI 2.17-7.48) were the leading morbidities associated with mortality after 42 days. Conclusion Women who experience severe maternal morbidity have an accelerated risk of mortality beyond the postpartum period compared with women who do not experience severe morbidity. More intensive clinical follow-up may be merited for women with serious pregnancy complications.

Background: Severe maternal morbidity is rising, yet the association with cardiovascular disease is not clear. We examined the risk of cardiovascular hospitalization up to 3 decades after having a pregnancy complicated by severe maternal morbidity. Methods: We analyzed a longitudinal cohort of 1 336 846 women who were pregnant between 1989 and 2019 in Quebec, Canada. The main exposure measure was severe maternal morbidity in any pregnancy, including severe preeclampsia, acute renal failure, sepsis, and other life-threatening conditions. Using time-varying Cox regression models, we compared the adjusted risk of hospitalization for cardiovascular disease up to 3 decades after pregnancy for women with severe maternal morbidity relative to women without severe morbidity. Results: Five percent of women had severe maternal morbidity. Overall, there were 68 287 cardiovascular hospitalizations during 21 725 672 person-years of follow-up in the cohort. Compared with no morbidity, women with any severe morbidity had a greater risk of cardiovascular hospitalization (hazard ratio [HR], 1.77 [95% CI, 1.72–1.82]). The association was the greatest within the first year of delivery (HR, 4.42 [95% CI, 3.77–5.19]) but persisted beyond 15 years (HR, 1.44 [95% CI, 1.37–1.51]). Having a cardiac complication (HR, 5.37 [95% CI, 4.65–6.20]), cerebrovascular accident (HR, 3.82 [95% CI, 2.94–4.96]), or acute renal failure (HR, 2.60 [95% CI, 2.15–3.14]) during pregnancy was strongly associated with future cardiovascular hospitalization. Conclusions: Women with severe maternal morbidity have a greater risk of cardiovascular disease after pregnancy, both in the short and long term. These women may benefit from active surveillance for cardiovascular disease.

Cocaine is associated with acute cardiovascular complications, but the long-term cardiovascular risks of cocaine use are poorly understood. We examined the association between cocaine use disorders and long-term cardiovascular morbidity in women.We analyzed a longitudinal cohort of 1,296,463 women in Quebec, Canada between 1989 and 2020. The exposure included cocaine use disorders prior to or during pregnancy. The outcome was cardiovascular hospitalization up to 31 years later. We used adjusted Cox regression models to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the association of cocaine use disorders with cardiovascular hospitalization.The cohort included 2954 women with cocaine use disorders. Compared with women without an identified cocaine disorder, women with cocaine use disorders had 1.55 times greater risk of future cardiovascular hospitalization during 3 decades of follow-up (95% CI, 1.37-1.75). Cocaine use disorders were strongly associated with inflammatory heart disease (HR 4.82; 95% CI, 2.97-7.83), cardiac arrest (HR 2.93; 95% CI, 1.46-5.88), valve disease (HR 3.09; 95% CI, 2.11-4.51), and arterial embolism (HR 2.22; 95% CI, 1.19-4.14). The association between cocaine use disorder and cardiovascular hospitalization was most marked after 5 to 10 years of follow-up (HR 2.15; 95% CI, 1.70-2.72).Women with cocaine use disorders have a high risk of cardiovascular hospitalization up to 3 decades later. Substance use reduction and cardiovascular risk surveillance may help reduce the burden of cardiovascular disease in women with cocaine use disorders.

While restrictive abortion laws still prevail in most low- and middle-income countries (LMICs), many countries have reformed their abortion laws, expanding the grounds on which abortion can be performed legally. However, the implications of these reforms on women’s access to and use of health services, as well as their health outcomes, are uncertain. This systematic review aimed to evaluate and synthesize empirical research evidence concerning the effects of abortion law reforms on women’s health services and health outcomes in LMICs. We searched Medline, Embase, CINAHL and Web of Science databases, as well as grey literature and reference lists of included studies. We included pre–post and quasi-experimental studies that aimed to estimate the causal effect of a change in abortion law on at least one of four outcomes: (1) use of and access to abortion services, (2) fertility rates, (3) maternal and/or neonatal morbidity and mortality and (4) contraceptive use. We assessed the quality of studies using the quasi-experimental study design series checklist and synthesized evidence through a narrative description. Of the 2796 records identified by our search, we included 13 studies in the review, which covered reforms occurring in Uruguay, Ethiopia, Mexico, Nepal, Chile, Romania, India and Ghana. Studies employed pre–post, interrupted time series, difference-in-differences and synthetic control designs. Legislative reforms from highly restrictive to relatively liberal were associated with reductions in fertility, particularly among women from 20 to 34 years of age, as well as lower maternal mortality. Evidence regarding the impact of abortion reforms on other outcomes, as well as whether effects vary by socioeconomic status, is limited. Further research is required to strengthen the evidence base for informing abortion legislation in LMICs. This review explicitly points to the need for rigorous quasi-experimental studies with sensitivity analyses to assess underlying assumptions. The systematic review was registered in PROSPERO database CRD42019126927.

Background A country’s abortion law is a key component in determining the enabling environment for safe abortion. While restrictive abortion laws still prevail in most low- and middle-income countries (LMICs), many countries have reformed their abortion laws, with the majority of them moving away from an absolute ban. However, the implications of these reforms on women’s access to and use of health services, as well as their health outcomes, is uncertain. First, there are methodological challenges to the evaluation of abortion laws, since these changes are not exogenous. Second, extant evaluations may be limited in terms of their generalizability, given variation in reforms across the abortion legality spectrum and differences in levels of implementation and enforcement cross-nationally. This systematic review aims to address this gap. Our aim is to systematically collect, evaluate, and synthesize empirical research evidence concerning the impact of abortion law reforms on women’s health services and outcomes in LMICs. Methods We will conduct a systematic review of the peer-reviewed literature on changes in abortion laws and women’s health services and outcomes in LMICs. We will search Medline, Embase, CINAHL, and Web of Science databases, as well as grey literature and reference lists of included studies for further relevant literature. As our goal is to draw inference on the impact of abortion law reforms, we will include quasi-experimental studies examining the impact of change in abortion laws on at least one of our outcomes of interest. We will assess the methodological quality of studies using the quasi-experimental study designs series checklist. Due to anticipated heterogeneity in policy changes, outcomes, and study designs, we will synthesize results through a narrative description. Discussion This review will systematically appraise and synthesize the research evidence on the impact of abortion law reforms on women’s health services and outcomes in LMICs. We will examine the effect of legislative reforms and investigate the conditions that might contribute to heterogeneous effects, including whether specific groups of women are differentially affected by abortion law reforms. We will discuss gaps and future directions for research. Findings from this review could provide evidence on emerging strategies to influence policy reforms, implement abortion services and scale up accessibility. Systematic review registration PROSPERO CRD42019126927

Background Suboptimal weight gain during pregnancy is a potentially modifiable risk factor. We aimed to investigate the association between suboptimal gestational weight gain and severe adverse birth outcomes by pre-pregnancy body mass index (BMI) categories, including obesity class I to III. Methods and findings We conducted a population-based study of pregnant women with singleton hospital births in Washington State, US, between 2004 and 2013. Optimal, low, and excess weight gain in each BMI category was calculated based on weight gain by gestational age as recommended by the American College of Obstetricians and Gynecologists and the Institute of Medicine. Primary composite outcomes were (1) maternal death and/or severe maternal morbidity (SMM) and (2) perinatal death and/or severe neonatal morbidity. Logistic regression was used to obtain adjusted odds ratios (AORs) and 95% confidence intervals. Overall, 722,839 women with information on pre-pregnancy BMI were included. Of these, 3.1% of women were underweight, 48.1% had normal pre-pregnancy BMI, 25.8% were overweight, and 23.0% were obese. Only 31.5% of women achieved optimal gestational weight gain. Women who had low weight gain were more likely to be African American and have Medicaid health insurance, while women with excess weight gain were more likely to be non-Hispanic white and younger than women with optimal weight gain in each pre-pregnancy BMI category. Compared with women who had optimal weight gain, those with low gestational weight gain had a higher rate of maternal death, 7.97 versus 2.63 per 100,000 (p = 0.027). In addition, low weight gain was associated with the composite adverse maternal outcome (death/SMM) in women with normal pre-pregnancy BMI and in overweight women (AOR 1.12, 95% CI 1.04–1.21, p = 0.004, and AOR 1.17, 95% CI 1.04–1.32, p = 0.009, respectively) compared to women in the same pre-pregnancy BMI category who had optimal weight gain. Similarly, excess gestational weight gain was associated with increased rates of death/SMM among women with normal pre-pregnancy BMI (AOR 1.20, 95% CI 1.12–1.28, p < 0.001) and obese women (AOR 1.12, 95% CI 1.01–1.23, p = 0.019). Low gestational weight gain was associated with perinatal death and severe neonatal morbidity regardless of pre-pregnancy BMI, including obesity classes I, II, and III, while excess weight gain was associated with severe neonatal morbidity only in women who were underweight or had normal BMI prior to pregnancy. Study limitations include the ascertainment of pre-pregnancy BMI using self-report, and lack of data availability for the most recent years. Conclusions In this study, we found that most women do not achieve optimal weight gain during pregnancy. Low weight gain was associated with increased risk of severe adverse birth outcomes, and in particular with maternal death and perinatal death. Excess gestational weight gain was associated with severe adverse birth outcomes, except for women who were overweight prior to pregnancy. Weight gain recommendations for this group may need to be reassessed. It is important to counsel women during pregnancy about specific risks associated with both low and excess weight gain., In a population-based retrospective cohort study, Ugochinyere Vivian Ukah and colleagues investigate the association between gestational weight gain and severe adverse birth outcomes in Washington State, USA., Author summary Why was this study done? The Institute of Medicine (IOM) has guidelines for optimal weight gain during pregnancy for women who have normal body mass index (BMI) and those who are underweight, overweight, and obese prior to pregnancy. Suboptimal weight gain is associated with adverse health outcomes for the mother and baby. The prevalence of obesity is rising, yet knowledge gaps exist in gestational weight gain recommendations specifically for women with various degrees of obesity (class I to III). Limited information is available about severe maternal and neonatal morbidity in women with suboptimal weight gain in each pre-pregnancy BMI category, particularly in class I to III obesity. What did the researchers do and find? We conducted a study including all 722,839 women with singleton delivery in Washington State, US, between 2004 and 2013, to assess birth outcomes associated with suboptimal weight gain. Less than half of women achieved the recommended optimal gestational weight gain. Low gestational weight gain was associated with an increase in adverse perinatal outcomes, particularly with maternal death and stillbirth, and with an increase in severe maternal morbidity in normal weight and overweight women. Excess gestational weight gain was associated with an increase in adverse maternal and perinatal outcomes in women with pre-pregnancy BMI within or below the normal range; such association was not observed in women who were overweight prior to pregnancy, while severe maternal morbidity was elevated in obese women with excess weight gain. Among obese women, low weight gain was associated with perinatal death and/or severe neonatal morbidity in all obesity classes, while excess weight gain was associated with adverse maternal and perinatal outcomes in women who had class III obesity. What do these findings mean? The IOM weight gain recommendations for women who are overweight prior to pregnancy may need reassessment. Weight gain below the recommended range in women who are obese prior to pregnancy may increase the risk of perinatal death/severe neonatal morbidity. Low weight gain may potentially be used as a marker of elevated risk of stillbirth; however, further studies are needed to assess such utility.

Background The hypertensive disorders of pregnancy are a leading cause of maternal and perinatal mortality and morbidity. The ability to predict these complications using simple tests could aid in management and improve outcomes. We aimed to systematically review studies that reported on potential predictors of adverse maternal outcomes among women with a hypertensive disorder of pregnancy. Methods We searched MEDLINE, Embase and CINAHL (inception - December 2016) for studies of predictors of severe maternal complications among women with a hypertensive disorder of pregnancy. Studies were selected in a two-stage process by two independent reviewers, excluding those reporting only on adverse fetal outcomes. We extracted data on study and test(s) characteristics and outcomes. Accuracy of prediction was assessed using sensitivity, specificity, likelihood ratios and area under the receiver operating curve (AUROC). Strong evidence of prediction was taken to be a positive likelihood ratio >10 or a negative likelihood ratio

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

In well-resourced settings, reduced circulating maternal-free placental growth factor (PlGF) aids in either predicting or confirming the diagnosis of preeclampsia, fetal growth restriction, stillbirth, preterm birth, and delivery within 14 days of testing when preeclampsia is suspected. This blinded, prospective cohort study of maternal plasma PlGF in women with suspected preeclampsia was conducted in antenatal clinics in Maputo, Mozambique. The primary outcome was the clinic-to-delivery interval. Other outcomes included: confirmed diagnosis of preeclampsia, transfer to higher care, mode of delivery, intrauterine fetal death, preterm birth, and low birth weight. Of 696 women, 95 (13.6%) and 601 (86.4%) women had either low (P =0.0042). Also, low PlGF was associated with a confirmed diagnosis of preeclampsia, higher blood pressure, transfer for higher care, earlier gestational age delivery, delivery within 7 and 14 days, preterm birth, cesarean delivery, lower birth weight, and perinatal loss. In urban Mozambican women with symptoms or signs suggestive of preeclampsia, low maternal plasma PlGF concentrations are associated with increased risks of adverse pregnancy outcomes, whether the diagnosis of preeclampsia is confirmed. Therefore, PlGF should improve the provision of precision medicine to individual women and improve pregnancy outcomes for those with preeclampsia or related placenta-mediated complications.

The fullPIERS model is a risk prediction model developed to predict adverse maternal outcomes within 48 h for women admitted with pre-eclampsia. External validation of the model is required before implementation for clinical use. We assessed the temporal and external validity of the fullPIERS model in high income settings using five cohorts collected between 2003 and 2016, from tertiary hospitals in Canada, the United States of America, Finland and the United Kingdom. The cohorts were grouped into three datasets for assessing the primary external, and temporal validity, and broader transportability of the model. The predicted risks of developing an adverse maternal outcome were calculated using the model equation and model performance was evaluated based on discrimination, calibration, and stratification. Our study included a total of 2429 women, with an adverse maternal outcome rate of 6.7%, 6.6%, and 7.0% in the primary external, temporal, and combined (broader) validation cohorts, respectively. The model had good discrimination in all datasets: 0.81 (95%CI 0.75-0.86), 0.82 (95%CI 0.76-0.87), and 0.75 (95%CI 0.71-0.80) for the primary external, temporal, and broader validation datasets, respectively. Calibration was best for the temporal cohort but poor in the broader validation dataset The likelihood ratios estimated to rule in adverse maternal outcomes were high at a cut-off of >= 30% in all datasets. The fullPIERS model is temporally and externally valid and will be useful in the management of women with pre-eclampsia in high income settings although model recalibration is required to improve performance, specifically in the broader healthcare settings.

Background Intensive care unit (ICU) outcome prediction models, such as Acute Physiology And Chronic Health Evaluation (APACHE), were designed in general critical care populations and their use in obstetric populations is contentious. The aim of the CIPHER (Collaborative Integrated Pregnancy High-dependency Estimate of Risk) study was to develop and internally validate a multivariable prognostic model calibrated specifically for pregnant or recently delivered women admitted for critical care. Methods A retrospective observational cohort was created for this study from 13 tertiary facilities across five high-income and six low- or middle-income countries. Women admitted to an ICU for more than 24 h during pregnancy or less than 6 weeks post-partum from 2000 to 2012 were included in the cohort. A composite primary outcome was defined as maternal death or need for organ support for more than 7 days or acute life-saving intervention. Model development involved selection of candidate predictor variables based on prior evidence of effect, availability across study sites, and use of LASSO (Least Absolute Shrinkage and Selection Operator) model building after multiple imputation using chained equations to address missing data for variable selection. The final model was estimated using multivariable logistic regression. Internal validation was completed using bootstrapping to correct for optimism in model performance measures of discrimination and calibration. Results Overall, 127 out of 769 (16.5%) women experienced an adverse outcome. Predictors included in the final CIPHER model were maternal age, surgery in the preceding 24 h, systolic blood pressure, Glasgow Coma Scale score, serum sodium, serum potassium, activated partial thromboplastin time, arterial blood gas (ABG) pH, serum creatinine, and serum bilirubin. After internal validation, the model maintained excellent discrimination (area under the curve of the receiver operating characteristic (AUROC) 0.82, 95% confidence interval (CI) 0.81 to 0.84) and good calibration (slope of 0.92, 95% CI 0.91 to 0.92 and intercept of −0.11, 95% CI −0.13 to −0.08). Conclusions The CIPHER model has the potential to be a pragmatic risk prediction tool. CIPHER can identify critically ill pregnant women at highest risk for adverse outcomes, inform counseling of patients about risk, and facilitate bench-marking of outcomes between centers by adjusting for baseline risk. Electronic supplementary material The online version of this article (10.1186/s13054-018-2215-6) contains supplementary material, which is available to authorized users.

Supplemental Digital Content is available in the text., The PlGF (placental growth factor) has been largely demonstrated to be associated with the diagnosis of the hypertensive disorders of pregnancy (HDPs); however, it is unclear how useful it is for the prognosis of the condition. Our objective was to provide a summary of important findings of its prognostic ability by systematically reviewing studies that examined the ability of the PlGF, either independently or combined with other factors, to predict maternal and fetal complications resulting from the HDPs. We included studies published before January 30, 2017, reporting on the use of the PlGF as a prognostic test for women with confirmed HDPs or suspected preeclampsia. Of the 220 abstracts identified through MEDLINE, Embase, and CINAHL (Cumulative Index to Nursing and Allied Health Literature), 17 studies were eligible for our review. Prognostic performance was evaluated by sensitivity, specificity, likelihood ratios, and area under the receiver operating characteristic curve. PlGF showed moderate-to-high evidence (likelihood ratios of ≥5 or ≤0.2 or area under the receiver operating characteristic curves ≥0.70) for identifying women at the highest risk of preterm delivery or neonatal outcomes (10/12 studies) but showed no clinically useful performance for the prediction of adverse maternal outcomes. PlGF may aid in the management of women with HDPs to avert fetal complications. Future studies should determine an optimum threshold for the marker to guide delivery and should examine whether its use for predicting adverse maternal outcomes in women with HDPs can be improved.

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.

In well-resourced settings, reduced circulating maternal free placental growth factor (PlGF) aids in either predicting or confirming the diagnosis of preeclampsia, fetal growth restriction, stillbirth, preterm birth, and delivery within 14 days of testing when pre-eclampsia is suspected. This operational pilot implementation of maternal plasma PlGF in women with suspected preeclampsia was conducted in six antenatal clinics in Maputo, Mozambique (six control clinics for comparison). The primary outcome was transfer to higher levels of care, following the informative PlGF assay. Of antenatal visits, 133/31,993 (0·42%) and 20/33,841 (0·06%) resulted in pre-eclampsia-related transfers of care for women attending intervention and control clinics, respectively (p < 0·0001). The clinic-to-delivery for women with low PlGF (

Objectives To evaluate the performance of the Modified Early Obstetric Warning System (MEOWS) to predict maternal ICU admission in an obstetric population. Design Case-control study. Setting Two maternity units in Vancouver, Canada, one with ICU facilities, between January 1, 2000, and December 31, 2011. Patients Pregnant or recently delivered (≤6 weeks) women admitted to the hospital for >24 hours. Three control patients were randomly selected per case and matched for year of admission. Measurements and Main Results Retrospective, observational, case-control validation study investigating the physiologic predictors of admission in the 24-hour period preceding either ICU admission >24 hours (cases) or following admission (control patients). Model performance was assessed based on sensitivity, specificity, and predictive values. Forty-six women were admitted to the ICU for >24 hours (0.51/1000 deliveries); the study included 138 randomly selected control patients. There were no maternal deaths in the cohort. MEOWS had high sensitivity (0.96) but low specificity (0.54) for ICU admission >24 hours, whereas ≥1 one red trigger maintained sensitivity (0.96) and improved specificity (0.73). Conclusion Altering MEOWS trigger parameters may improve the accuracy of MEOWS in predicting ICU admission. Formal modelling of a MEOWS scoring system is required to support evidence-based care.

Objective: To develop and internally validate a prognostic model for perinatal death that could guide community-based antenatal care of women with a hypertensive disorder of pregnancy (HDP) in low-resourced settings as part of a mobile health application.Study design: Using data from 1688 women (110 (6.5%) perinatal deaths) admitted to hospital after 32 weeks gestation with a HDP from five low-resourced countries in the miniPIERS prospective cohort, a logistic regression model to predict perinatal death was developed and internally validated. Model discrimination, calibration, and classification accuracy were assessed and compared with use of gestational age alone to determine prognosis.Main outcome measures: Stillbirth or neonatal death before hospital discharge.Results: The final model included maternal age; a count of symptoms (0, 1 or >= 2); and dipstick proteinuria. The area under the receiver operating characteristic curve was 0.75 [95% CI 0.71-0.80]. The model correctly identified 42/110 (38.2%) additional cases as high-risk (probability >15%) of perinatal death compared with use of only gestational ageConclusion: Using simple, routinely collected measures during antenatal care, we can identify women with a HDP who are at increased risk of perinatal death and who would benefit from transfer to facility-based care. This model requires external validation and assessment in an implementation study to confirm performance. (C) 2015 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.

Table S1. CIPHER (Collaborative Integrated Pregnancy High-dependency Estimate of Risk) cohort collaborators and site contribution. Table S2. Patient characteristics and univariate analysis results generated through complete case analysis. Table S3. Characteristics of women with and without missing data. (DOCX 43Â kb)

Table S1. CIPHER (Collaborative Integrated Pregnancy High-dependency Estimate of Risk) cohort collaborators and site contribution. Table S2. Patient characteristics and univariate analysis results generated through complete case analysis. Table S3. Characteristics of women with and without missing data. (DOCX 43Â kb)