An Integrated Immuno-Clinical and Laboratory System for Predicting Multiple Organ Failure in Obstetric Sepsis.
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Abstract
Background. Early prediction of multiple organ failure in obstetric sepsis remains a critical unmet need in intensive care, as commonly used scoring systems, including SOFA, identify organ dysfunction only after its clinical manifestation and therefore lack predictive capability at the initial stages of the disease. Aim. To develop and validate an integrated immuno-clinical predictive model for early identification of multiple organ failure in patients with obstetric sepsis. Methods. A single-center clinical-analytical study including 100 patients with obstetric sepsis was performed. Patients were stratified according to the development of multiple organ failure. Clinical, laboratory, and immunological parameters of innate and adaptive immunity were analyzed. Independent predictors were identified using multivariable logistic regression. Based on the regression coefficients, an integrated scoring system (PREVAS) was constructed. Model performance was assessed using receiver operating characteristic (ROC) curve analysis with calculation of the area under the curve (AUC), sensitivity, and specificity... Results. Multiple organ failure developed in 38.0% of patients. Independent predictors included elevated lactate (OR≈2.5), procalcitonin (OR≈2.3), D-dimer (OR≈2.0), and creatinine (OR≈2.1), as well as immune-related variables, including decreased CD4⁺ lymphocytes (OR≈2.7), increased CD14⁺ monocytes (OR≈2.4), enhanced TLR4 expression (OR≈2.3), and an increased IL-6/IL-10 ratio (OR≈2.6), in combination with reduced HLA-DR expression (OR≈2.2) (p<0.05). The integrated PREVAS model demonstrated superior discriminative performance (AUC=0.825) compared to models based on isolated parameter groups. At the optimal threshold, sensitivity reached 82% and specificity 79%. Conclusion. The PREVAS model provides reliable early prediction of multiple organ failure in obstetric sepsis before overt clinical deterioration and represents a practical tool for risk stratification and timely intensification of therapeutic management...