Prediction Of Adverse Maternal Outcomes Research Articles

PanPIERS: A tool for risk prediction of adverse maternal outcomes for patients with pre-eclampsia using incomplete data

panPIERS: A tool for risk prediction of adverse maternal outcomes for patients with pre-eclampsia using incomplete data

Prediction of Adverse Maternal Outcomes in Women with Early-Onset Preeclampsia with Severe Features in Mexico: Validation of the Full-PIERS Model.

Validate the full-PIERS model in predicting adverse maternal outcomes in women with early-onset preeclampsia with severe features in our population. Retrospective cohort study. We applied the full-PIERS model on 130 women with severe early-onset preeclampsia who were treated at a second-level hospital in Nuevo León, México. We validated the full-PIERS model in its ability to discriminate through the AUROC. The full-PIERS model applied to the data obtained in our study had good discrimination, revealing an AUC of 0.718 (95% CI 0.515-0.921; P = 0.017). A cut-off of 7.95 was identified as the cut-off point with the best diagnostic performance, with the highest Youden index, presenting a sensitivity of 54.5% and specificity of 99.2% for the development of complications. The full-PIERS model can predict adverse maternal outcomes in women admitted to our hospital with severe early-onset preeclampsia within 48 hours of admission.

OP05_3. Time-of-disease risk prediction of adverse maternal outcomes of pre-eclampsia using artificial intelligence

OP05_3. Time-of-disease risk prediction of adverse maternal outcomes of pre-eclampsia using artificial intelligence

Perinatal and neonatal outcome in patients with preeclampsia.

Preeclampsia (PE) affects 2-5% of pregnant women. Hypertensive disorders of pregnancy are associated with adverse maternal and perinatal outcomes. This study included 88 women showing gestational hypertension (GH) or PE symptoms, and their newborns. The rate of FGR was 43% for mothers with PE, compared to 8% with GH. The association was significant, p = < 0.001 but with moderate strength, Cramer's V = 0.40. The risk of FGR increased nine times when PE occurred, as the odds ratio was 9.25 (CI: 2.46-34.83), p = 0.001. PE was associated with FGR risk if delivery time was less than 34 weeks compared to a delivery time of more than 34 weeks. This was 82% of FGR cases for < 34 weeks, compared with 35% of cases in > 34 group, (p = 0.001; Cramer's V = 0.50). PE was also associated (p = 0.01, Cramer's V = 0.27) with the type of delivery, as the caesarean section rate was 74%, compared to 50% in the GH group. This made it three times higher the likelihood of delivery by caesarean section, as the odds ratio was 3.10 (CI: 1.24-7.75), p=0,02. Delivery time was significantly (p < 0.001) shortened to 38 weeks (27-41), compared to 40 weeks (38-42) GH mothers. There was no distinction in median age for PE and GH mothers (p = 0.124). The overall clinical status of neonates was proportional despite the mother's PE. The sum of Apgar points in the first, and then the second to third minute, did not differ significantly, p = 0.370 and 0.560, respectively. The number of peripheral blood platelets and leucocytes was not reduced (p = 0.821 and 0.534) in infants when the mother suffered from PE. The prediction of adverse maternal outcomes from hypertensive diseases of pregnancy is key to optimal management, including the timing of delivery and planning for the most appropriate place of care.

Exploring digital health interventions for pregnant women at high risk for pre-eclampsia and eclampsia in low-income and-middle-income countries: a scoping review

ObjectiveTo explore digital health interventions that have been used to support pregnant women at high risk for pre-eclampsia/eclampsia (HRPE/E) in low-income and middle-income countries (LMICs).DesignScoping review.Data sourceEMBASE, MEDLINE, Cochrane Central...

Longitudinal Risk Adjustment for Maternal End-Organ Injury and Death

Objective To determine whether adjusting for healthcare utilization and comorbidity diagnosed in the year before delivery improves the prediction of adverse maternal outcomes. Methods The Truven Health MarketScan database was used to determine whether healthcare utilization and comorbidity diagnosed in the year before pregnancy improved prediction of acute organ injury or death during the delivery hospitalization through 30 days postpartum in this retrospective cohort study. In an initial model, we analyzed the risk for adverse outcomes controlling for underlying comorbidity, obesity, and demographic risk factors present during pregnancy. Subsequent models included diagnoses from the year before pregnancy as well as whether patients had emergency department encounters, inpatient hospitalizations, or received medications from a pharmacy. We compared risk estimates and whether prediction of acute organ injury or death improved with data from the year before pregnancy. Unadjusted and adjusted log-linear regression models were performed to demonstrate the association between exposures and outcomes with unadjusted (RR) and adjusted risk ratios (aRR) with 95% CIs as measures of effects. Logistic regression was performed to calculate the c-statistic of the adjusted models. Separate analyses were performed for patients with Medicaid and commercial insurance. An analysis of Medicaid patients by maternal race and ethnicity was performed to determine if diagnoses and utilization before pregnancy accounted for maternal disparities. Results A total of 740,002 patients were analyzed in this study. In unadjusted analyses of patients with commercial insurance, ≥2 compared to 0 emergency department encounters (RR = 1.82, 95% CI = 1.61, 2.07), ≥2 compared to 0 inpatient hospitalizations (RR = 4.43, 95% CI = 3.20, 6.13), and receipt of medications from ≥5 prescription groups compared to no prescriptions (RR = 1.97, 95% CI = 1.74, 2.24) were all associated with increased risk for acute organ injury or death. Higher underlying comorbidity and obesity were also associated with increased risk. These risks were attenuated in adjusted analyses but retained significance. Risk estimates were similar for patients with Medicaid insurance with the exception of receipt of medications from ≥5 prescription groups which was non-significant in adjusted analyses (aRR = 1.12, 95% CI = 0.90, 1.40). C-statistics from logistic regression models were similar for models with and without pre-pregnancy data. When race was added to the adjusted models, risk among black women in the adjusted models did not differ significantly from the unadjusted estimate. Conclusion ED encounters and inpatient admissions the year before pregnancy were associated with increased risk of adverse maternal outcomes. However, adding these risk factors to adjusted models did not meaningfully improve the amount of variance accounted for. Further research is indicated to determine to what degree longitudinal care quality is associated with maternal risk.

Placental growth factor for the prognosis of women with preeclampsia (fullPIERS model extension): context matters

BackgroundThe fullPIERS risk prediction model was developed to identify which women admitted with confirmed diagnosis of preeclampsia are at highest risk of developing serious maternal complications. The model discriminates well between women who develop (vs. those who do not) adverse maternal outcomes. It has been externally validated in several populations. We assessed whether placental growth factor (PlGF), a biomarker associated with preeclampsia risk, adds incremental value to the fullPIERS model.MethodsUsing a cohort of women admitted into tertiary hospitals in well-resourced settings (the USA and Canada), between May 2010 to February 2012, we evaluated the incremental value of PlGF added to fullPIERS for prediction of adverse maternal outcomes within 48 h after admission with confirmed preeclampsia. The discriminatory performance of PlGF and the fullPIERS model were assessed in this cohort using the area under the receiver’s operating characteristic curve (AUROC) while the extended model (fullPIERS +PlGF) was assessed based on net reclassification index (NRI) and integrated discrimination improvement (IDI) performances.ResultsIn a cohort of 541 women delivered shortly (< 1 week) after presentation, 8.1% experienced an adverse maternal outcome within 48 h of admission. Prediction of adverse maternal outcomes was not improved by addition of PlGF to fullPIERS (NRI: -8.7, IDI − 0.06). Discriminatory performance (AUROC) was 0.67 [95%CI: 0.59–0.75] for fullPIERS only and 0.67 [95%CI: 0.58–0.76]) for fullPIERS extended with PlGF, a performance worse than previously documented in fullPIERS external validation studies (AUROC > 0.75).ConclusionsWhile fullPIERS model performance may have been affected by differences in healthcare context between this study cohort and the model development and validation cohorts, future studies are required to confirm whether PlGF adds incremental benefit to the fullPIERS model for prediction of adverse maternal outcomes in preeclampsia in settings where expectant management is practiced.

Prediction of adverse maternal outcomes of early severe preeclampsia.

Assess soluble FMS-like tyrosine kinase-1/placental growth factor ratio (sFlt-1/PlGF) diagnostic accuracy for predicting adverse maternal outcome in patients with early severe preeclampsia, and whether its predictive performance is superior to full preeclampsia integrated estimate of risk score (PIERS). Prospective study enrolled patients with early severe preeclampsia (defined by American College of Obstetricians and Gynaecologists 2013 guidelines) admitted to the Clinic for Obstetrics and Gynaecology, Clinical Center of Serbia intensive care unit. Patients underwent delivery to terminate preeclampsia within 48h of admission. PIERS was generated and blood samples taken at admission. Multiple pregnancies and gestational ages outside 24-34weeks were excluded. sFlt-1 and PlGF serum concentrations were measured using Elecsys® assays and cobas e 601 analyser. Maternal complications were recorded for seven days post-delivery. Diagnostic accuracy (sensitivity and specificity), and predictive performance (receiver operating characteristic area under curve [AUC]) vs. PIERS, of sFlt-1/PlGF for predicting adverse maternal outcome. Of 89 patients enrolled, 61 were evaluable. Median frequency of adverse maternal outcomes within seven days of delivery was two. Median sFlt-1/PlGF and PIERS were 521·0 and 5·0%, respectively. sFlt-1/PlGF showed greater correlation with complication number than PIERS (Spearman's rho: 0·728 [p<0·001] and 0·134 [p=0·304], respectively). AUC for sFlt-1/PlGF and PIERS were 0·853 and 0·628, respectively. A 377·0 sFlt-1/PlGF cut-off was optimal for predicting complications (75·0% sensitivity; 92·3% specificity). sFlt-1/PlGF correlated more closely with number of adverse maternal outcomes than PIERS, and was a superior predictor of maternal complications.

Shock Index in the Prediction of Adverse Maternal Outcome.

WHO states that obstetric hemorrhage, hypertensive disorders of pregnancy and sepsis account for approximately 50% of maternal deaths worldwide. All these conditions are associated with changes in vital signs including blood pressure (BP) and heart rate (HR). Shock index (SI) is the ratio of HR to systolic BP. To evaluate role of shock index as an early indicator of adverse maternal outcomes and to determine the threshold points of SI for five adverse maternal outcomes. This was a prospective observational study on 1004 consecutively enrolled subjects presenting in labor. Vital signs and Shock Index were recorded. SI thresholds were analyzed with respect to obstetric complications and adverse outcomes. Parametric tests such as Chi-square, comparison of proportions, comparison of mean and ROC curve analysis were applied on the data. The mean SI value in the vaginal delivery group was 1.02 ± 0.26 and it was 0.95 ± 0.033 in the caesarean delivery group. The values of SI ((Mean and SD) for ICU admission were (1.23 (± 0.35)), for (MODS) it was (1.47 (± 0.84)), for blood transfusion > 4 units it was (1.15 (± 0.41)), for surgical intervention it was (1.58 (± 0.51)) and for maternal death (1.39 (± 0.85)). SI ≥ 1.4, had sensitivity 26.82% (21.09-33.19); specificity 100%(99.53-100), PPV was 100% and NPV was 82.96%(81.8-84.06)with an AUC of 0.8 (0.78-0.83) on ROC analysis. In subjects with PIH/eclampsia, SI was lower and in patients with severe anemia, SI was higher. SI performed well as a screening tool in the prediction of adverse maternal outcomes. SI ≥ 0.9 was significantly associated with maternal adverse outcomes: ICU admission, MODS, surgical intervention, blood transfusion and death. The study proposes an SI cut-off of 0.9 for referral and a cut-off of 1.1 for intervention in a tertiary care hospital. Patients with PIH/eclampsia tend to have lower mean SI values as compared to the rest of the study population, suggesting that SI may not be a reliable indicator in patients with PIH/eclampsia.

Prediction of adverse maternal outcomes in preeclampsia at term.

Preeclampsia complicates 5-8% of all pregnancies and is associated with high rates of maternal and perinatal morbidity. The majority of cases occur at term gestations where the baby can be safely delivered. The preeclampsia disease process however can progress in the mother resulting in significant morbidity. In this study we were interested in examining the number of patients developing preeclampsia with severe features at term. We also investigated whether factors at admission might be predictive of disease progression. We performed a retrospective cohort study at a tertiary obstetric hospital in Melbourne, Australia from 2015 to 2017. There were 124 participants presenting with preeclampsia at term and included in our study. After admission, 44.4% progressed to preeclampsia with severe features. Disease features at admission associated with disease progression were chronic hypertension, elevated systolic blood pressure, reduced haemoglobin and elevated creatinine. Using predictive modelling, we determined that a combination of these features showed good discrimination (area under ROC = 0.88 (95% confidence interval 0.82-0.94)) with good performance (negative predictive value 80% and positive predictive value 87%) for predicting progression to preeclampsia with severe features. Almost half of the women presenting with preeclampsia at term will progress to preeclampsia with severe features. Admission characteristics can be used to predict those at risk of disease progression.

Comparison of performance of shock index and conventional vital sign parameters for prediction of adverse maternal outcomes following major postpartum hemorrhage in Abakaliki, Southeast Nigeria

Background: Despite advances in care, postpartum hemorrhage has continued to contribute disproportionately to maternal morbidity and mortality in developing countries due to delayed and/or substandard care in the diagnosis and management of hypovolemic shock. Aim: To compare the performance of the shock index with conventional vital signs for prediction of maternal outcome following postpartum hemorrhage and to establish alert thresholds for use in low-resource settings. Materials and Method: This is a 7-year retrospective cohort study of 289 women treated for primary postpartum hemorrhage at the Alex Ekwueme Federal University Teaching Hospital, Abakaliki. The data for systolic and diastolic blood pressure, mean arterial pressure, pulse pressure, heart rate, and shock index measured at the time of diagnosis of postpartum hemorrhage were analyzed. Adverse maternal outcomes such as intensive care unit admission, blood transfusion ≥5 units, hemoglobin level <7 g/dL, surgical interventions, end-organ failure, and death were reviewed. The area under the receiver operating characteristic curve (AUROC) for each vital sign was used to predict adverse maternal outcomes. Sensitivity, specificity, and negative and positive predictive values were calculated to determine the thresholds of the best predictor. Results: Shock index had the highest AUROC to predict invasive surgical procedures (0.70 for SI [95% CI 0.66–0.80] compared with 0.69 [95% CI 0.61–0.76] for pulse rate). Shock index was a consistent superior predictor for other outcomes. Shock index (SI) ≥0.9 had 100% sensitivity (95% CI 74.6–100) and 46.7% specificity (95% CI 34.9–56.5) for prediction of intensive care admission, and SI ≥1.7 had 46.9% sensitivity (95% CI 19.8–62.8) and 98.9% specificity (CI 91.1–100) for prediction of maternal death. Conclusion: Shock index is a consistent superior predictor of adverse maternal outcomes following postpartum hemorrhage when compared with conventional vital signs. SI <0.9 provides reassurance, whereas SI ≥1.7 indicates a need for urgent intervention to prevent maternal mortality.

1011: What is the optimal maternal Vitamin D level for the prediction of adverse maternal outcomes?

1011: What is the optimal maternal Vitamin D level for the prediction of adverse maternal outcomes?

Temporal and external validation of the fullPIERS model for the prediction of adverse maternal outcomes in women with pre-eclampsia.

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.

Prediction of adverse maternal outcomes from pre-eclampsia and other hypertensive disorders of pregnancy: A systematic review.

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. 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 <0.1, and for multivariable models, an AUROC ≥0.70. Bivariate random effects models were used to summarise performance when possible. Of 32 studies included, 28 presented only model development and four examined external validation. Tests included symptoms and signs, laboratory tests and biomarkers. No single test was a strong independent predictor of outcome. The most promising prediction was with multivariable models, especially when oxygen saturation, or chest pain/dyspnea were included. Future studies should investigate combinations of tests in multivariable models (rather than single predictors) to improve identification of women at high risk of adverse outcomes in the setting of the hypertensive disorders of pregnancy.

Placental Growth Factor as a Prognostic Tool in Women With Hypertensive Disorders of Pregnancy: A Systematic Review.

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.

Vital Sign Prediction of Adverse Maternal Outcomes in Women with Hypovolemic Shock: The Role of Shock Index.

ObjectiveTo determine the optimal vital sign predictor of adverse maternal outcomes in women with hypovolemic shock secondary to obstetric hemorrhage and to develop thresholds for referral/intensive monitoring and need for urgent intervention to inform a vital sign alert device for low-resource settings.Study DesignWe conducted secondary analyses of a dataset of pregnant/postpartum women with hypovolemic shock in low-resource settings (n = 958). Using receiver-operating curve analysis, we evaluated the predictive ability of pulse, systolic blood pressure, diastolic blood pressure, shock index, mean arterial pressure, and pulse pressure for three adverse maternal outcomes: (1) death, (2) severe maternal outcome (death or severe end organ dysfunction morbidity); and (3) a combined severe maternal and critical interventions outcome comprising death, severe end organ dysfunction morbidity, intensive care admission, blood transfusion ≥ 5 units, or emergency hysterectomy. Two threshold parameters with optimal rule-in and rule-out characteristics were selected based on sensitivities, specificities, and positive and negative predictive values.ResultsShock index was consistently among the top two predictors across adverse maternal outcomes. Its discriminatory ability was significantly better than pulse and pulse pressure for maternal death (p<0.05 and p<0.01, respectively), diastolic blood pressure and pulse pressure for severe maternal outcome (p<0.01), and systolic and diastolic blood pressure, mean arterial pressure and pulse pressure for severe maternal outcome and critical interventions (p<0.01). A shock index threshold of ≥ 0.9 maintained high sensitivity (100.0) with clinical practicality, ≥ 1.4 balanced specificity (range 70.0–74.8) with negative predictive value (range 93.2–99.2), and ≥ 1.7 further improved specificity (range 80.7–90.8) without compromising negative predictive value (range 88.8–98.5).ConclusionsFor women with hypovolemic shock from obstetric hemorrhage, shock index was consistently a strong predictor of all adverse outcomes. In lower-level facilities in low resource settings, we recommend a shock index threshold of ≥ 0.9 indicating need for referral, ≥ 1.4 indicating urgent need for intervention in tertiary facilities and ≥ 1.7 indicating high chance of adverse outcome. The vital sign alert device incorporated values 0.9 and 1.7; however, all thresholds will be prospectively validated and clinical pathways for action appropriate to setting established prior to clinical implementation.

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

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. 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. 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. 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.

Prediction of Adverse Maternal Outcomes in Preeclampsia

Prediction of Adverse Maternal Outcomes in Preeclampsia

Prediction of Adverse Maternal Outcomes in Preeclampsia: Development and Validation of the FullPIERS Model

ABSTRACT Maternal deaths from preeclampsia primarily result in cases with eclampsia, uncontrolled hypertension, or progressing HELLP syndrome. Delivery is the only cure for preeclampsia. Management strategies involve determination of risk factors to predict which pregnancies are at high risk for adverse maternal outcomes. Previous attempts to develop risk assessment models that could identify potential predictive risk factors for adverse outcomes occurring at any time after admission with preeclampsia have been unsuccessful. The aim of this prospective multicenter study was to develop and internally validate a preeclampsia outcome prediction model—the fullPIERS (Preeclampsia Integrated Estimate of RiSk) model that could identify serious or fatal complications in women with preeclampsia or who developed the disorder within 48 hours of hospital admission. Between 2003 and 2010, data for 2023 women from 8 international sites were entered into the fullPIERS database. The primary study outcome was maternal mortality or other serious complications of preeclampsia. A stepwise backward elimination logistic regression model incorporating routinely reported and informative variables was used to predict adverse maternal outcome. Standard methods were used to calculate the area under the curve (AUC) of the receiver operating characteristic (ROC). Of the 2023 women with preeclampsia, 261 (13%) had adverse outcomes at any time after hospital admission and 106 (5%) had adverse outcomes within 48 hours of admission. Predictors in the fullPIERS model associated with adverse maternal outcome included gestational age at eligibility, chest pain or dyspnea, oxygen saturation, creatinine, platelet counts, and aspartate transaminase. Analysis of the fullPIERS model showed that the model predicted adverse maternal outcomes within the first 48 hours of eligibility; the AUC ROC was 0.88, with a 95% confidence interval, 0.84–0.92. Additionally, fullPIERS was also predictive of adverse maternal outcomes up to 7 days after eligibility (AUC ROC >0.7). Identification of women at high risk of preeclampsia complications at 48 hours to 7 days after admission may help guide clinical care and management of these women. Over time this may lead to development of new treatments and interventions that may reduce the risk of life-altering or life-ending complications such as stroke or end-organ damage.

Prediction of adverse maternal outcomes in pre-eclampsia: development and validation of the fullPIERS model

Pre-eclampsia is a leading cause of maternal deaths. These deaths mainly result from eclampsia, uncontrolled hypertension, or systemic inflammation. We developed and validated the fullPIERS model with the aim of identifying the risk of fatal or life-threatening complications in women with pre-eclampsia within 48 h of hospital admission for the disorder. We developed and internally validated the fullPIERS model in a prospective, multicentre study in women who were admitted to tertiary obstetric centres with pre-eclampsia or who developed pre-eclampsia after admission. The outcome of interest was maternal mortality or other serious complications of pre-eclampsia. Routinely reported and informative variables were included in a stepwise backward elimination regression model to predict the adverse maternal outcome. We assessed performance using the area under the curve (AUC) of the receiver operating characteristic (ROC). Standard bootstrapping techniques were used to assess potential overfitting. 261 of 2023 women with pre-eclampsia had adverse outcomes at any time after hospital admission (106 [5%] within 48 h of admission). Predictors of adverse maternal outcome included gestational age, chest pain or dyspnoea, oxygen saturation, platelet count, and creatinine and aspartate transaminase concentrations. The fullPIERS model predicted adverse maternal outcomes within 48 h of study eligibility (AUC ROC 0·88, 95% CI 0·84-0·92). There was no significant overfitting. fullPIERS performed well (AUC ROC >0·7) up to 7 days after eligibility. The fullPIERS model identifies women at increased risk of adverse outcomes up to 7 days before complications arise and can thereby modify direct patient care (eg, timing of delivery, place of care), improve the design of clinical trials, and inform biomedical investigations related to pre-eclampsia. Canadian Institutes of Health Research; UNDP/UNFPA/WHO/World Bank Special Programme of Research, Development, and Research Training in Human Reproduction; Preeclampsia Foundation; International Federation of Obstetricians and Gynecologists; Michael Smith Foundation for Health Research; and Child and Family Research Institute.