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A Predictive Model for Disseminated Intravascular Coagulopathy in Sepsis: An Observational Study
Yaojie Fu1, Yujing He2, Caixia Zheng3
1Emergency Department, The First Affiliated Hospital of Xiamen University, Xiamen, Fujian, People's Republic of China.
Insights
A new predictive model can identify Disseminated Intravascular Coagulopathy (DIC) in sepsis patients. This tool aids clinicians in early detection and intervention for better patient outcomes.
Area of Science:
- Critical Care Medicine
- Hematology
- Infectious Diseases
Background:
- Sepsis is a major global health concern with high mortality.
- Disseminated Intravascular Coagulopathy (DIC) is a severe complication of sepsis, increasing mortality and healthcare costs.
- Existing prognostic tools lack specificity for predicting DIC in sepsis patients.
Purpose of the Study:
- To develop and validate a novel predictive model for early Disseminated Intravascular Coagulopathy (DIC) detection in sepsis patients.
- To identify key clinical and laboratory parameters associated with DIC development in sepsis.
- To compare the predictive performance of the new model against the SOFA score.
Main Methods:
- An observational study was conducted with 336 sepsis patients.
- Clinical and laboratory data, including platelet count (PLT), prothrombin time (PT), lactate (LAC), and procalcitonin (PCT), were collected.
- Risk factors for DIC were identified through univariate and multivariate analyses, and a predictive model was constructed.
Main Results:
- Patients with DIC exhibited lower PLT and higher PT, LAC, and PCT levels.
- Key predictors identified were PLT (OR = 0.985), PT (OR = 1.140), and LAC (OR = 1.101).
- The developed model demonstrated a superior Area Under the ROC Curve (0.850) compared to the SOFA score (0.813), with 84.4% sensitivity and 75.0% specificity for DIC prediction.
Conclusions:
- A novel, effective risk prediction model for DIC in sepsis patients has been developed.
- The model aids clinicians in identifying high-risk individuals for timely intervention.
- Early detection of DIC in sepsis can potentially improve patient outcomes and reduce mortality.
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.
