Pre-eclampsia/eclampsia are leading causes of maternal mortality and morbidity, particularly in low- and middle- income countries (LMICs). We developed the miniPIERS risk prediction model to provide ...a simple, evidence-based tool to identify pregnant women in LMICs at increased risk of death or major hypertensive-related complications.
From 1 July 2008 to 31 March 2012, in five LMICs, data were collected prospectively on 2,081 women with any hypertensive disorder of pregnancy admitted to a participating centre. Candidate predictors collected within 24 hours of admission were entered into a step-wise backward elimination logistic regression model to predict a composite adverse maternal outcome within 48 hours of admission. Model internal validation was accomplished by bootstrapping and external validation was completed using data from 1,300 women in the Pre-eclampsia Integrated Estimate of RiSk (fullPIERS) dataset. Predictive performance was assessed for calibration, discrimination, and stratification capacity. The final miniPIERS model included: parity (nulliparous versus multiparous); gestational age on admission; headache/visual disturbances; chest pain/dyspnoea; vaginal bleeding with abdominal pain; systolic blood pressure; and dipstick proteinuria. The miniPIERS model was well-calibrated and had an area under the receiver operating characteristic curve (AUC ROC) of 0.768 (95% CI 0.735-0.801) with an average optimism of 0.037. External validation AUC ROC was 0.713 (95% CI 0.658-0.768). A predicted probability ≥25% to define a positive test classified women with 85.5% accuracy. Limitations of this study include the composite outcome and the broad inclusion criteria of any hypertensive disorder of pregnancy. This broad approach was used to optimize model generalizability.
The miniPIERS model shows reasonable ability to identify women at increased risk of adverse maternal outcomes associated with the hypertensive disorders of pregnancy. It could be used in LMICs to identify women who would benefit most from interventions such as magnesium sulphate, antihypertensives, or transportation to a higher level of care.
Preeclampsia is a leading cause of maternal morbidity. The clinical challenge lies in predicting which women with preeclampsia will suffer adverse outcomes and would benefit from treatment, while ...minimizing potentially harmful interventions. Our aim was to determine the ability of maternal symptoms (i.e., severe nausea or vomiting, headache, visual disturbance, right upper quadrant pain or epigastric pain, abdominal pain or vaginal bleeding, and chest pain or dyspnea) to predict adverse maternal or perinatal outcomes.
We used data from the PIERS (Pre-eclampsia Integrated Estimate of RiSk) study, a multicentre, prospective cohort study designed to investigate the maternal risks associated with preeclampsia. Relative risks and receiver operating characteristic (ROC) curves were assessed for each preeclampsia symptom and outcome pair.
Of 2023 women who underwent assessment, 52% experienced at least one preeclampsia symptom, with 5.2% and 5.3% respectively experiencing an adverse maternal or perinatal outcome. No symptom and outcome pair, in either of the maternal or perinatal groups, achieved an area under the ROC curve value > 0.7, which would be necessary to demonstrate a discriminatory predictive value.
Maternal symptoms of preeclampsia are not independently valid predictors of maternal adverse outcome. Caution should be used when making clinical decisions on the basis of symptoms alone in the preeclamptic patient.
Platelet count has been proposed as a screening test for generalized coagulopathy in women with preeclampsia. We performed this study to determine the relationship between platelet counts and the ...risk of abnormal coagulation and adverse maternal outcomes in women with preeclampsia.
We used data from women in the PIERS (Pre-eclampsia Integrated Estimate of RiSk) database. Abnormal coagulation was defined as either an international normalized ratio result greater than and/or a serum fibrinogen level less than the BC Women's Hospital laboratory's pregnancy-specific normal range. The relationship between platelet counts and adverse maternal outcomes was explored using a logistic regression analysis. The sensitivity, specificity, positive predictive value, and negative predictive value of platelet counts in identifying abnormal coagulation or adverse maternal outcomes were calculated.
Abnormal coagulation occurred in 105 of 1405 eligible women (7.5%). The odds of having abnormal coagulation were increased for women with platelet counts < 50 × 10(9)/L (OR 7.78; 95% CI 3.36 to 18.03) and between 50 and 99 × 10(9)/L (OR 2.69; 95% CI 1.44 to 5.01) compared with women who had platelet counts above 150 × 10(9)/L. Platelet counts < 100 × 10(9)/L were associated with significantly increased odds of adverse maternal outcomes, most specifically blood transfusion. A platelet count of < 100 × 10(9)/L had good specificity in identifying abnormal coagulation and adverse maternal outcomes (92% 95% CI 91% to 94% and 92% 95% CI 91% to 94%, respectively), but poor sensitivity (22% 95% CI 15% to 31% and 16% 95% CI 11% to 23%, respectively).
A platelet count < 100 × 10(9)/L is associated with an increased risk of abnormal coagulation and maternal adverse outcomes in women with preeclampsia. However, the platelet count should not be used in isolation to guide care because of its poor sensitivity. Whether or not a platelet count is normal should not be used to determine whether further coagulation tests are needed.
We sought to determine the role of respiratory assessment by cardiorespiratory symptoms and/or oxygen saturation by pulse oximetry (SpO2) in predicting adverse maternal outcomes in women admitted to ...hospital with preeclampsia.
These data derive from an international, prospective multicentre cohort study, PIERS (Pre-eclampsia Integrated Estimate of RiSk), which assesses predictors of adverse outcomes in women admitted to tertiary perinatal units with preeclampsia. Univariate and multivariate analyses of cardiorespiratory symptoms and pulse oximetry were performed to assess their ability to predict a combined adverse maternal outcome developed through international Delphi consensus.
SpO2 successfully predicted adverse maternal outcomes; the area under the receiver-operator characteristic curve (AUC ROC) was 0.71 (95% CI 0.65 to 0.77). Combining the symptoms of chest pain and/or dyspnea with pulse oximetry improved this predictive ability (AUC ROC 0.73; 95% CI 0.67 to 0.78). When SpO2 was stratified into risk groups using inflection points on the ROC curve, the highest risk group (SpO2 90% to 93%) had an odds ratio of 18.1 (95% CI 8.2 to 40.2) for all outcomes within 48 hours when compared with the baseline group (SpO2 98% to 100%).
Assessing SpO2 aids in the assessment of maternal risk in women admitted to hospital with preeclampsia. An SpO2 value of ≤ 93% confers particular risk. The symptom complex of chest pain and/or dyspnea adds to the association.
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.
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.
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%).
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.
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.
Background Pre-eclampsia/eclampsia are leading causes of maternal mortality and morbidity, particularly in low- and middle- income countries (LMICs). We developed the miniPIERS risk prediction model ...to provide a simple, evidence-based tool to identify pregnant women in LMICs at increased risk of death or major hypertensive-related complications. Methods and Findings From 1 July 2008 to 31 March 2012, in five LMICs, data were collected prospectively on 2,081 women with any hypertensive disorder of pregnancy admitted to a participating centre. Candidate predictors collected within 24 hours of admission were entered into a step-wise backward elimination logistic regression model to predict a composite adverse maternal outcome within 48 hours of admission. Model internal validation was accomplished by bootstrapping and external validation was completed using data from 1,300 women in the Pre-eclampsia Integrated Estimate of RiSk (fullPIERS) dataset. Predictive performance was assessed for calibration, discrimination, and stratification capacity. The final miniPIERS model included: parity (nulliparous versus multiparous); gestational age on admission; headache/visual disturbances; chest pain/dyspnoea; vaginal bleeding with abdominal pain; systolic blood pressure; and dipstick proteinuria. The miniPIERS model was well-calibrated and had an area under the receiver operating characteristic curve (AUC ROC) of 0.768 (95% CI 0.735-0.801) with an average optimism of 0.037. External validation AUC ROC was 0.713 (95% CI 0.658-0.768). A predicted probability ≥25% to define a positive test classified women with 85.5% accuracy. Limitations of this study include the composite outcome and the broad inclusion criteria of any hypertensive disorder of pregnancy. This broad approach was used to optimize model generalizability. Conclusions The miniPIERS model shows reasonable ability to identify women at increased risk of adverse maternal outcomes associated with the hypertensive disorders of pregnancy. It could be used in LMICs to identify women who would benefit most from interventions such as magnesium sulphate, antihypertensives, or transportation to a higher level of care. Please see later in the article for the Editors' Summary
Abstract Introduction Pre-eclampsia is associated with increased risk to both the mother and fetus. Effective monitoring of the fetal condition is essential to the management of women with ...pre-eclampsia. The biophysical profile (BPP) is one monitoring tool available to clinicians. Aims and Objectives To compare the BPP test with cardiotocography/non-stress test (CTG/NST) alone for their ability to predict fetal acidemia at birth or a composite adverse perinatal outcome among women with preeclampsia and to estimate the effect of BPP assessment on mode of delivery and birth outcome. Methods Secondary analysis of a prospective cohort of women with preeclampsia. The predictive ability of the tests was assessed based on sensitivity, specificity, positive and negative likelihood ratios (LR+, LR−). Women assessed with the BPP were compared with matched controls not assessed with the BPP to determine the odds of Cesarean delivery or adverse perinatal outcomes after adjustment for potential confounders. Results Five out of 89 women (5.6%) had an abnormal BPP; 18 out of 89 (20.2%) had an abnormal CTG/NST. Fetal acidemia was diagnosed in 13 fetuses (14.6%); composite adverse perinatal outcome in 68 fetuses/infants (76.4%). Both tests had relatively poor predictive performance for both outcomes (LR+ between 2.50 and 3.90 and LR− between 0.64 and 0.93). Assessment with the BPP was positively associated with fetal acidemia (adjusted OR 4.84; 95% CI 1.33–17.66). Conclusion The BPP and CTG/NST alone were poor predictors of perinatal outcome in this cohort; multiple tests should be considered when assessing fetal risk in women with preeclampsia.
PDF
