AI Summary & Key Takeaways
AI InsightConclusion: The FSI ratio is a simple, rapid, and effective marker for predicting severe placental abruption and may improve early risk stratification in clinical practice.
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Abstract
Aims: To evaluate the predictive value of the fibrinogen-to-shock index (FSI) ratio for identifying severe placental abruption and to compare its performance with fibrinogen and shock index alone. Methods: This retrospective cohort study included 136 pregnant women diagnosed with placental abruption at a tertiary perinatology center. Patients were classified as having mild/moderate abruption (n=86) or severe abruption (n=50). Demographic, clinical, laboratory, maternal, and neonatal outcome data were analyzed. The shock index was calculated as heart rate divided by systolic blood pressure, and the FSI ratio was derived by dividing fibrinogen by shock index. Univariate and multivariate logistic regression analyses were performed to determine predictors of severe abruption. Receiver operating characteristic (ROC) analysis, Youden index-based cut-off analysis, and decision curve analysis were used to assess discriminative performance and clinical utility. Results: Patients with severe placental abruption had significantly lower hemoglobin and fibrinogen levels and a significantly higher shock index than those with mild/moderate abruption (all p<0.001). The FSI ratio was markedly lower in the severe group (p<0.001). In multivariate analysis, the FSI ratio remained the only independent predictor of severe placental abruption (adjusted OR 0.20, 95% CI 0.11-0.36; p<0.001). ROC analysis showed excellent predictive performance for the FSI ratio (AUC 0.970, 95% CI 0.930-0.997), with an optimal cut-off value of ≤2.89, yielding 94.0% sensitivity and 96.5% specificity. Decision curve analysis also demonstrated favorable net benefit across clinically relevant threshold probabilities. Conclusion: The FSI ratio is a simple, rapid, and effective marker for predicting severe placental abruption and may improve early risk stratification in clinical practice.