ArticleInternational journal of general medicine2024
A Predictive Model for Disseminated Intravascular Coagulopathy in Sepsis: An Observational Study.
Article in International journal of general medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Biomarkers and clinical factors associated with sepsis-induced coagulopathy: A systematic review and meta-analysis.Science progress · 2026Pooled it
- CEBPD-MMP8 Axis Contributes to Cardiomyocyte Injury in Septic Shock.Applied biochemistry and biotechnology · 2026Article
- Interpretable machine learning model for early prediction of disseminated intravascular coagulation in critically ill children.Scientific reports · 2025Article
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Authors and funding
5 authors.
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Abstract
Introduction: Sepsis remains a significant global health challenge due to its high morbidity and mortality rates. Disseminated Intravascular Coagulopathy (DIC) represents a critical complication of sepsis, contributing to increased mortality and economic burden. Despite various prognostic scoring systems, there is a lack of a specific model for DIC prediction in sepsis patients. Methods: This observational study included 336 sepsis patients. Clinical and laboratory data were collected, and prognoses were defined according to established criteria. Results: We enrolled 336 patients, with 304 in the non-DIC group and 32 in the DIC group. Patients with DIC had notably lower platelet (PLT) and higher levels of prothrombin time (PT), lactate (LAC), and procalcitonin (PCT) compared to those without DIC. Univariate and multivariate analyses identified risk factors associated with the DIC, showing that PLT (OR = 0.985, 95% CI 0.978-0.993, p < 0.001), PT level (OR = 1.140, 95% CI 1.004-1.295, p = 0.044), and LAC (OR = 1.101, 95% CI 0.989-1.226, p = 0.078) were related factors. A risk model was established, and its sensitivity and specificity in predicting DIC among sepsis patients were assessed by comparing it to the SOFA score. The area under the ROC curve for the model was 0.850, while the SOFA score was 0.813. With a model score >-2.12, the sensitivity for predicting DIC was 84.4%, and the specificity was 75.0%. Conclusion: Our study introduces a predictive model for DIC detection in sepsis patients, emphasizing the need for clinicians to focus on patients with high model scores for timely intervention.
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