External Validation of the fullPIERS Risk Prediction Model in a U.S. Cohort of Individuals with Preeclampsia

This study aimed to externally validate the Preeclampsia Integrated Estimate of Risk (fullPIERS) risk prediction model in a cohort of pregnant individuals with preeclampsia in the United States.This was a retrospective study of individuals with preeclampsia who delivered at 22 weeks or greater from January 1, 2010, to December 31, 2020. The primary outcome was a composite of maternal mortality or other serious complications of preeclampsia occurring within 48 hours of admission. We calculated the probability of the composite outcome using the fullPIERS prediction model based on data available within 12 hours of admission, including gestational age, chest pain or dyspnea, serum creatinine levels, platelet count, aspartate transaminase levels, and oxygen saturation. We assessed the model performance using the area under the curve (AUC) of the receiver operating characteristic curve. The optimal cutoff point was determined using Liu's method. A calibration plot was used to evaluate the model's goodness-of-fit.Among 1,510 individuals with preeclampsia, 82 (5.4%) experienced the composite outcome within 48 hours. The fullPIERS model achieved an AUC of 0.80 (95% confidence interval [CI]: 0.75-0.86). The predicted probability for individuals with the composite outcome (median: 18.8%; interquartile range: 2.9-59.1) was significantly higher than those without the outcome (median: 0.9%; interquartile range: 0.4-2.7). The optimal cutoff point of 5.5% yielded a sensitivity of 70.7% (95% CI: 59.6-80.3), a specificity of 85% (95% CI: 82.7-86.5), a positive likelihood ratio of 4.6 (95% CI: 3.8-5.5), and an odds ratio of 13.3 (95% CI: 8.1-21.8). The calibration plot indicated that the model underestimated risk when the predicted probability was below 1% and overestimated risk when the predicted probability exceeded 5%.The fullPIERS model demonstrated good discrimination in this U.S. cohort of individuals with preeclampsia, suggesting it may be a useful tool for health care providers to identify individuals at risk for severe complications. · The fullPIERS risk prediction model has not been validated in a U.S. cohort.. · The model showed good predictive accuracy (AUC: 0.80) for severe maternal complications but had calibration issues at extreme-risk levels.. · This study confirms the fullPIERS model's applicability in the United States..

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Publication Details

Journal
American Journal of Perinatology
Published
2024-10-28
DOI
https://doi.org/10.1055/a-2452-8220
Primary Topic
Pregnancy and preeclampsia studies
Type
article
Field-Weighted Citation Impact
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article

External Validation of the fullPIERS Risk Prediction Model in a U.S. Cohort of Individuals with Preeclampsia

Kari Flicker, Aref Rastegar, Madeleine Wright, Maya Vishnia et al.
American Journal of Perinatology
Pregnancy and preeclampsia studies
article

External Validation of the fullPIERS Risk Prediction Model in a U.S. Cohort of Individuals with Preeclampsia

Kari Flicker, Aref Rastegar, Madeleine Wright, Maya Vishnia, Tetsuya Kawakita, Lauren Gilgannon, Lea Nehme, Danielle Long, Neha Gupta, Rohini Kousalya Siva, Matilda Francis, Kenyone S. King
article en

Abstract

This study aimed to externally validate the Preeclampsia Integrated Estimate of Risk (fullPIERS) risk prediction model in a cohort of pregnant individuals with preeclampsia in the United States.This was a retrospective study of individuals with preeclampsia who delivered at 22 weeks or greater from January 1, 2010, to December 31, 2020. The primary outcome was a composite of maternal mortality or other serious complications of preeclampsia occurring within 48 hours of admission. We calculated the probability of the composite outcome using the fullPIERS prediction model based on data available within 12 hours of admission, including gestational age, chest pain or dyspnea, serum creatinine levels, platelet count, aspartate transaminase levels, and oxygen saturation. We assessed the model performance using the area under the curve (AUC) of the receiver operating characteristic curve. The optimal cutoff point was determined using Liu's method. A calibration plot was used to evaluate the model's goodness-of-fit.Among 1,510 individuals with preeclampsia, 82 (5.4%) experienced the composite outcome within 48 hours. The fullPIERS model achieved an AUC of 0.80 (95% confidence interval [CI]: 0.75-0.86). The predicted probability for individuals with the composite outcome (median: 18.8%; interquartile range: 2.9-59.1) was significantly higher than those without the outcome (median: 0.9%; interquartile range: 0.4-2.7). The optimal cutoff point of 5.5% yielded a sensitivity of 70.7% (95% CI: 59.6-80.3), a specificity of 85% (95% CI: 82.7-86.5), a positive likelihood ratio of 4.6 (95% CI: 3.8-5.5), and an odds ratio of 13.3 (95% CI: 8.1-21.8). The calibration plot indicated that the model underestimated risk when the predicted probability was below 1% and overestimated risk when the predicted probability exceeded 5%.The fullPIERS model demonstrated good discrimination in this U.S. cohort of individuals with preeclampsia, suggesting it may be a useful tool for health care providers to identify individuals at risk for severe complications. · The fullPIERS risk prediction model has not been validated in a U.S. cohort.. · The model showed good predictive accuracy (AUC: 0.80) for severe maternal complications but had calibration issues at extreme-risk levels.. · This study confirms the fullPIERS model's applicability in the United States..

American Journal of PerinatologyVol. 42(08)
MedStar Washington Hospital Center (US), University of Virginia (US), Case Western Reserve University (US), Old Dominion University (US)
Eastern Virginia Medical School
Good health and well-being
Openalex Percentile: Top 70%
Pregnancy and preeclampsia studies
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