脑出血患者静脉血栓栓塞症风险预测模型的构建及验证研究

doi:10.3761/j.issn.2096-7446.2025.09.003

Abstract

Abstract:

Objective To develop and validate a risk prediction model for venous thromboembolism（VTE） in patients with intracerebral hemorrhage（ICH） and compare its predictive ability with Caprini score. Methods The modeling group retrospectively selected ICH patients from the Medical Information Mart for Intensive Care-IV （MIMIC-IV） database（2008—2019）. Risk factors were identified using univariate and logistic regression analyses，and a risk prediction model was established. Internal validation was conducted using the bootstrap resampling method. The validation group retrospectively selected ICH patients in a tertiary hospital in China from 2016 to 2024 for external validation and compared it with the Caprini score. Results ICU length of stay（OR=1.064），absolute lymphocyte count（OR=0.711），and BMI（OR=1.932） were identified as the three independent risk factors for VTE in ICH patients. In the modeling group，the model demonstrated an AUC of 0.767，with a sensitivity of 0.718 and specificity of 0.684. The Hosmer-Lemeshow test indicated good calibration（χ²=3.075，P= 0.930）. In the external validation group，the model achieved an AUC of 0.785，AUC of the Caprini score was 0.608. Conclusion This prediction model has good predictive performance and can provide theoretical basis for clinical medical staff to early identify high-risk VTE populations in ICH patients.

Key words: Cerebral Hemorrhage, Venous Thromboembolism, Nomogram, Risk Prediction Model, Nursing

YE Hongmin, GAN Xiuni, GAO Yan, ZHANG Huan, ZHOU Wen, LI Dongxue. Development and validation of a risk prediction model for venous thromboembolism in patients with intracerebral hemorrhage[J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(9): 1042-1049.

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Development and validation of a risk prediction model for venous thromboembolism in patients with intracerebral hemorrhage

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