Predictive model for low-molecular-weight heparin ineffectiveness in pregnant and postpartum women with intracranial venous sinus thrombosis: a multicenter study.

OBJECTIVE: To develop a risk prediction model for low-molecular-weight heparin (LMWH) ineffectiveness in pregnant women with intracranial venous sinus thrombosis (CVST), enabling early identification of high-risk patients. METHODS: A retrospective analysis was conducted on 221 pregnant or postpartum CVST patients treated with LMWH at seven Chinese hospitals between January 2010 and January 2025. Patients were divided into effective (191 cases) and ineffective (30 cases) treatment groups. Logistic regression identified predictors, which were then used to develop a risk prediction model. RESULTS: Univariate analysis revealed significant factors associated with treatment ineffectiveness: Coronavirus Disease 2019 (COVID-19), hyperthyroidism, platelet (PLT) count, antithrombin III (AT-III), homocysteine (Hcy), low-density lipoprotein cholesterol (LDL-C), protein C, and protein S (all P < 0.1). Variables with a P-value < 0.1 were further analyzed using Least Absolute Shrinkage and Selection Operator (LASSO) regression to identify key predictors, with the lambda value (0.011) determining the final model. Multivariate analysis identified independent risk factors: COVID-19, protein S, and homocysteine. Protein S (odds ratio [OR] < 1) acted as a protective factor, while COVID-19 and homocysteine (OR > 1) were risk factors. The model's receiver operating characteristic (ROC) curve area was 0.930 (95% confidence interval [CI]: 0.882-0.979), with sensitivity of 0.867 and specificity of 0.885. Cross-validation and bootstrap validation demonstrated robust model performance, with areas under the curve of 0.919 and 0.909, respectively. CONCLUSIONS: The developed predictive model, incorporating COVID-19, protein S, and Hcy, effectively assesses the risk of LMWH ineffectiveness in pregnant women with CVST, supporting clinical decision-making.