Analysis of Risk Factors and the Establishment of a Predictive Model for Thrombosis in Patients with immune thrombocytopenia

Objectives To explore the risk factors for thrombi occurring in patients with immune thrombocytopenia (ITP) and establish a risk prediction model to better predict the risk of thrombosis in patients with ITP. Methods We retrospectively analyzed 350 ITP patients who had been hospitalized in The First People's Hospital of Yunnan Province between January 2020 and June 2024. For all patients, we recorded demographic characteristics and clinical data, analyzed the risk factors for thrombosis in ITP patients and then developed a risk prediction model. Results Stepwise logistic regression analysis indicated that a high complement D- dimer level, a low PLT and a high Padua score were independent risk factors for thrombosis in ITP patients. According to multivariate analysis, a predictive model for thrombus risk was successfully established; the area under the ROC curve(AUC) was 0.673 (95% CI: 0.615-0.730) and the maximum Youden index, sensitivity and specificity were 0.272, 47.0% and 80.2%, respectively. Conclusion A high complement D-dimer level, low PLT level, and a high Padua score were shown to be independent risk factors for thrombosis in ITP patients. We developed a risk prediction model based on these three risk factors that could predict the risk of thrombosis in ITP patients to some extent.