Nomogram for predicting disseminated intravascular coagulation in heatstroke patients: A 10 years retrospective study

BACKGROUND: Disseminated intravascular coagulation (DIC) can lead to multiple organ failure and death in patients with heatstroke. This study aimed to identify independent risk factors of DIC and construct a predictive model for clinical application. METHODS: This retrospective study included 87 patients with heatstroke who were treated in the intensive care unit of our hospital from May 2012 to October 2022. Patients were divided into those with DIC (n = 23) or without DIC (n = 64). Clinical and hematological factors associated with DIC were identified using a random forest model, least absolute shrinkage and selection operator (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE). Overlapping factors were used to develop a nomogram model, which was diagnostically validated. Survival at 30 days after admission was compared between patients with or without DIC using Kaplan-Meier analysis. RESULTS: Random forest, LASSO, and SVM-RFE identified a low maximum amplitude, decreased albumin level, high creatinine level, increased total bilirubin, and aspartate transaminase (AST) level as risk factors for DIC. Principal component analysis confirmed that these independent variables differentiated between patients who experienced DIC or not, so they were used to construct a nomogram. The nomogram showed good predictive power, with an area under the receiver operating characteristic curve of 0.976 (95% CI 0.948–1.000) and 0.971 (95% CI, 0.914–0.989) in the internal validation. Decision curve analysis indicated clinical utility for the nomogram. DIC was associated with significantly lower 30 days survival for heatstroke patients. CONCLUSION: A nomogram incorporating coagulation-related risk factors can predict DIC in patients with heatstroke and may be useful in clinical decision-making.