ArticleArchives of academic emergency medicine2026
Independent Predictors of Major Adverse Cardiac and Hepatic Outcomes Following Acute Liver Complications of Pregnancy; A Retrospective Cohort Study.
Article in Archives of academic emergency medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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12 authors.
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Abstract
Introduction: Acute liver complications of pregnancy (ALCP) remain major contributors to maternal morbidity. This study aimed to characterize cardio-hepatic crosstalk and identify independent predictors of hepatic failure and major cardiovascular events in patients with ALCP. Methods: This retrospective cohort study was conducted to investigate cardio-hepatic crosstalk, endothelial dysfunction, and cardiovascular risk stratification among pregnant women with ALCP (4 diagnostic categories: HELLP syndrome, pre-eclampsia with hepatic involvement, acute fatty liver of pregnancy, and intrahepatic cholestasis of pregnancy). Independent predictors of cardiac and hepatic outcomes following ALCP, among endothelial, cardiac, inflammatory, coagulation, and renal biomarkers, were detected using correlation, multivariable regression, and receiver operating characteristic (ROC) analyses. Results: 400 patients with ALCP were studied. All 22 studied biomarkers differed significantly across diagnostic categories. The ratio of soluble fms-like tyrosine kinase-1 to placental growth factor (sFlt-1/PlGF ratio) correlated most strongly with N-terminal pro-B-type natriuretic peptide (NT-proBNP) (r = 0.57, p < 0.001) and independently predicted major cardiovascular events (adjusted odds ratio (OR) = 1.38, 95% confidence interval (CI) = 1.03-1.85). C-reactive protein and creatinine independently predicted hepatic failure, with C-reactive protein showing the highest discriminative accuracy (area under the ROC curve of 0.79 (95% CI: 0.69-0.89). Conclusions: Hepatic and cardiovascular derangement in ALCP constitute an interconnected, biomarker-detectable syndrome, supporting integrated biomarker-guided risk stratification for emergency management and delivery-timing decisions.
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