Abstract
INTRODUCTION: Venous thromboembolism (VTE) is an important complication after spontaneous intracerebral hemorrhage (ICH). However, it remains a clinical challenge to identify individuals at high risk for VTE in a population with ICH. This study aimed to develop a model integrating cardiac biomarkers with clinical-radiological factors for predicting VTE risk in patients with spontaneous ICH. METHODS: ICH patients were retrospectively enrolled between October 2019 and December 2022. Baseline clinical characteristics, laboratory data, and radiological features were collected. Patients with pulmonary embolism (PE) and deep vein thrombosis were classified into the VTE group. Cox regression analysis was used to identify independent predictors of in-hospital VTE. A nomogram was developed based on the multivariate model, and its performance was evaluated using the concordance index (C-index), decision curve analysis, and net reclassification improvement. RESULTS: A total of 170 patients (mean age: 54.66 ± 13.6 years, 125 [73.5%] males) with ICH were included in the analysis. Thirty-six (21.2%) patients were assigned to the VTE group. Multivariate Cox analysis identified age (HR = 1.032, 95% CI: 1.002-1.062, p = 0.033), baseline edema volume (HR = 1.034, 95% CI: 1.012-1.056, p = 0.002), intraventricular hemorrhage (HR = 3.268, 95% CI: 1.635-6.530, p < 0.001), myoglobin (Myo; HR = 1.002, 95% CI: 1.000-1.003, p = 0.010), and B-type natriuretic peptide (BNP; HR = 1.003, 95% CI: 1.001-1.006, p = 0.007) as independent predictors. The combined model showed better predictive performance than the clinical-radiological model alone (C-index: 0.791 vs. 0.749). The nomogram demonstrated good calibration and clinical utility across a wide risk threshold range. CONCLUSION: Myo and BNP provide incremental predictive value for VTE risk stratification in ICH patients beyond traditional factors. The developed nomogram offers a practical tool for individualized risk assessment, potentially guiding optimized VTE prophylaxis strategies.