Prediction Study of VTE Risk in Patients with Acute Cerebral Hemorrhage in Neurosurgery Based on Clinical Indicators and Modified Caprini Model

Corresponding author: Liuchao

DOI: 10.12201/bmr.202607.00019

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  Abstract: Abstract Objective To analyze the independent risk factors of venous thromboembolism (VTE) in patients with acute intracerebral hemorrhage in neurosurgery, and to construct and validate a modified Caprini risk assessment model for patients with intracerebral hemorrhage based on the above factors. ?Methods? A retrospective analysis was performed on 312 patients with acute intracerebral hemorrhage admitted to the neurosurgery department of a tertiary Class A hospital in Zhejiang Province from January 2022 to December 2023. The patients were divided into a control group (non-thrombosis group, n=156) and an observation group (thrombosis group, n=156) according to whether VTE occurred. Baseline data, clinical indicators and intervention measures of the two groups were collected. Statistically significant variables were first screened by univariate analysis, and then independent risk factors of VTE were determined by multivariate Logistic regression analysis. A prediction model was constructed based on the screened core variables, and the discrimination (receiver operating characteristic curve, ROC) and stability (5-fold cross-validation) of the model were evaluated. ?Results? The results of multivariate Logistic regression analysis showed that elevated D-dimer (OR=12.486, 95%CI: 5.225-29.838, P<0.05), motor deficit (OR=3.373, 95%CI: 2.157-5.274, P<0.05), ischemic intracerebral hemorrhage (OR=2.146, 95%CI: 1.223-3.766, P<0.05) and infection (OR=2.380, 95%CI: 1.607-3.524, P<0.05) were independent risk factors for VTE in patients with intracerebral hemorrhage. The modified prediction model constructed based on the above 5 core variables showed high prediction efficiency in the test set: accuracy 81.91%, precision 82.61%, recall 80.85%, F1 score 81.72%, and the area under the curve (AUC) reached 0.882. The average AUC of 5-fold cross-validation was 0.883 (±0.068), which proved that the model had good discrimination and stability. ?Conclusion? Advanced age, elevated D-dimer, motor deficit, ischemic intracerebral hemorrhage and infection are the key risk factors for VTE in patients with acute intracerebral hemorrhage in neurosurgery. The modified prediction model containing the above specific clinical indicators constructed in this study has good clinical application value, can more accurately identify patients at high risk of VTE, and provides a quantitative basis for individualized prevention

  Key words: Venous Thromboembolism；Cerebral Hemorrhage；Risk Factor；Prediction Model；Caprini Model

  Submit time: 10 July 2026

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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