Background: 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.
Methods: 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.
Findings: 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.
Interpretation: 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.
Funding: 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.
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http://dx.doi.org/10.1016/S0140-6736(10)61351-7 | DOI Listing |
Am J Perinatol
November 2024
Department of Obstetrics and Gynecology, Macon and Joan Brock Virginia Health Sciences at Old Dominion University (ODU), Norfolk, Virginia.
Objective: 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.
Study Design: 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.
EClinicalMedicine
October 2024
Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Cureus
August 2024
Community Medicine and Family Medicine, All India Institute of Medical Sciences, Kalyani, Kalyani, IND.
Introduction: Preeclampsia, characterized by hypertensive disorders and systemic inflammatory response, remains a leading cause of maternal morbidity and mortality globally. Effective risk assessment tools are crucial for predicting adverse maternal outcomes.
Objective: This study evaluates the performance of the fullPIERS (Preeclampsia Integrated Estimate of Risk) model in predicting adverse maternal outcomes within 24 hours of admission for preeclampsia.
Obstet Gynecol Int
May 2024
Department of Obstetrics, Hospital Regional Materno Infantil del Estado de Nuevo León, Monterrey 67140, Mexico.
Objective: Validate the full-PIERS model in predicting adverse maternal outcomes in women with early-onset preeclampsia with severe features in our population.
Methods: 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.
Lancet Digit Health
April 2024
Department of Obstetrics and Gynaecology, University of British Columbia, Vancouver, BC, Canada; Department of Women and Children's Health, School of Life Course and Population Sciences, King's College London, London UK. Electronic address:
Background: 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.
Methods: 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.
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