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

Payne, Beth; Hodgson, Sam; Hutcheon, Jennifer A.; Joseph, K. S.; Li, J; Lee, T; Magee, Laura A.; Qu, Zhi; Dadelszen, Peter von

doi:10.1111/j.1471-0528.2012.03496.x

Cited by 43 publications

(45 citation statements)

References 9 publications

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“…According to the authors of the fullPIERS study [6], among the 1935 women for whom complete data were available, 65 % of women were stratified as low-risk, with a predicted probability of adverse outcome below 0.025, and at the other end of the risk spectrum were the 4 % at highest risk, with a predicted probability of 0.30 or greater. Only 1 % of women in the low-risk category experienced an adverse outcome, compared with 59 % of those in the high-risk category.…”

Section: Discussionmentioning

confidence: 99%

“…This tool helps to determine the maternal risks in the setting of preeclampsia and to decide for triage, transport, and treatment along with assessment of neonatal risk based on gestational age at presentation [6]. The goal of the PIERS model was to develop and validate an outcome prediction tool that identifies which hospitalized women with preeclampsia will suffer adverse maternal or perinatal outcome.…”

Section: Introductionmentioning

confidence: 99%

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

Agrawal

Maitra

2015

J Obstet Gynecol India

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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 v 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 Sp O 2 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 C30 %) showed excellent performance (i.e., 17.5) of fullPIERS model as a rule in test.Shruti Agrawal is a Third-Year Resident; Nandita Maitra is a Professor and Head. 123 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.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Agrawal

Maitra

2015

J Obstet Gynecol India

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“…Such factors may result in case-mix differences and may also alter the effect of the predictors on the outcome. 2,7 Therefore, the extreme predictions observed in the calibration slope may have been as a result of differences in the predictor effects in the validation and development cohorts. 10 These factors may have resulted in the reduced performance of the model.…”

Section: Main Findingsmentioning

confidence: 99%

“…Using the worst values (predefined in the model development study as the highest or lowest where appropriate) 7 for the model predictors recorded within 24 hours of admission to HDP, the fullPIERS equation was applied to the miniPIERS data, and the predicted probability of adverse outcomes for each individual with complete predictor data (complete case) was calculated. Before assessing the performance of the model, the model intercept was updated (baseline adjustment) 10 because of the difference in the adverse maternal outcome rates between the fullPIERS (6.5%) and the miniPIERS population (12.5%).…”

Section: Statistical Analysesmentioning

confidence: 99%

“…6,7 A preliminary external validation using the PETRA study (Preeclampsia Eclampsia Trial) cohort of highrisk women was also reassuring (AUC ROC: 0.97; 95% CI, 0.94-0.99). 8 To ensure the generalizability of the fullPIERS model before it is implemented into clinical practice to improve maternal care, 9,10 we sought to assess the model's potential for use in a LMIC setting where the majority of HDP-related morbidity and mortality occur.…”

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confidence: 99%

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

et al. 2017

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H ypertension during pregnancy is one of the top 3 causes of maternal morbidity and mortality worldwide.1,2 The hypertensive disorders of pregnancy (HDPs), which include preeclampsia, superimposed preeclampsia, gestational hypertension, and chronic hypertension, complicate ≈5% to 10% of pregnancies. 1,3 Maternal complications that result from HDPs include stroke, eclampsia, and renal dysfunction; and adverse fetal outcomes include stillbirth, preterm delivery, and cerebral palsy. 4 These severe consequences of the HDPs make them a global health burden, especially in the low-and middle-income countries (LMICs) where >90% of HDP-related deaths occur. 2,5 To reduce this burden, there is a need to correctly identify women at high risk of developing adverse outcomes in time to avoid their occurrence. Accurate risk assessment can aid decision making around the management of HDPs, including timing of delivery, administration of antenatal corticosteroids for acceleration of fetal pulmonary maturity or Magnesium sulfate for seizure prophylaxis, and maternal transfer to a higher level of care. 1,3 To facilitate risk stratification and improve the management of HDPs, the fullPIERS model (Preeclampsia Integrated Estimate of Risk) was developed to predict adverse maternal outcomes occurring in the 48 hours after hospital admission with preeclampsia in high-income countries. The adverse outcomes predicted by the model included major organ dysfunction and death. 6 The fullPIERS model is based on maternal demographics, signs, symptoms, and laboratory tests, with the final model consisting of 6 predictor variables: gestational Abstract-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. To ensure the generalizability of the fullPIERS model before it is implemented into clinical practice to improve maternal care, 9,10 we sought to assess the model's potential for use in a LMIC setting where the majority of HDP-related morbidity and mortality occur. The objective of this st...

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Validation of fullPIERS model for prediction of adverse outcomes among women with severe pre‐eclampsia

Almeida

Katz

Coutinho

et al. 2017

Intl J Gynecology & Obste

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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

Cited by 43 publications

References 9 publications

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

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

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

Validation of fullPIERS model for prediction of adverse outcomes among women with severe pre‐eclampsia

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