ArticleCureus2024
Prediction of Adverse Maternal Outcomes in Preeclampsia Using the FullPIERS (Preeclampsia Integrated Estimate of Risk) Model in a Tertiary Care Hospital of Eastern India.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- The Turkish validation of the fullPIERS model to predict adverse maternal and fetal outcomes in preeclamptic pregnancies.Frontiers in medicine · 2026Article
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4 authors.
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Abstract
introductionPreeclampsia, 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.
objectiveThis 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.
methodsA cross-sectional study was conducted over one year, involving 100 preeclamptic patients admitted to Nil Ratan Sircar Medical College & Hospital (NRSMCH). Predictor variables were collected within 24 hours of admission and analyzed using the fullPIERS model.
resultsThe fullPIERS model effectively stratified maternal risk. Adverse outcomes were significantly associated with systolic blood pressure (BP) ≥ 140 mmHg, diastolic BP ≥ 90 mmHg, oxygen saturation ≤ 95%, frontal headache, visual disturbances, chest pain/dyspnea, and abnormal random blood sugar, albumin, alanine aminotransferase, platelet count, and creatinine levels. A fullPIERS score ≥ 30 was strongly predictive of adverse maternal outcomes.
conclusionThe fullPIERS model is a valuable tool for predicting adverse maternal outcomes in preeclampsia, aiding in timely and effective clinical decision-making.
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