The development and validation of a risk prediction model for lower extremity deep venous thrombosis in elderly patients with intracerebral hemorrhage
YAN Feifan1, LI Yun1, MA Pengyan2, YIN Qiang3, LU Zhongqiu4
1.Department of Neurology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325015, China; 2.Department of Vascular Surgery, the First Affiliated Hospital of Wenzhou Medical University,Wenzhou 325015, China; 3.Department of Geriatrics, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325015, China; 4.Department of Emergency Medicine, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325015, China
YAN Feifan,LI Yun,MA Pengyan, et al. The development and validation of a risk prediction model for lower extremity deep venous thrombosis in elderly patients with intracerebral hemorrhage[J]. JOURNAL OF WEZHOU MEDICAL UNIVERSITY, 2022, 52(4): 277-282.
Abstract：Objective: To develop and verify the risk prediction model of lower extremity deep vein thrombosis (DVT) in elderly patients with intracerebral hemorrhage (ICH). Methods: The clinical data of 953 elderly ICH in-patients in the First Affiliated Hospital of Wenzhou Medical University from January 2016 to December 2020 were collected. DVT associated risk factors of these patients were screened according to univariate analysis and multivariate Logistic regression analysis, after which the risk prediction model was established and the nomogram was drawn. The area under the ROC curve was used to evaluate the predictive effect of the model,and the Bootstrap method was used to internally verify the prediction model. Results: The multivariate regression analysis showed that age, sex, season, disturbance of consciousness, left lower limb muscle strength and D-dimer concentration were independent risk factors of lower limb DVT in elderly patients with intracerebral hemorrhage.The area under ROC curve of the prediction model is 0.766, with the sensitivity 70.5%, specificity 71.4%, Youden index 0.418, and the internal validation C-index 0.758. Conclusion: This model can effectively predict the occurrence of lower limb DVT in elderly patients with intracerebral hemorrhage, and provide basis for clinical medical staff to identify high-risk patients and take measures in time.
