Guoji laonian yixue zazhi (Jan 2024)

Establishment of Risk Model of Postoperative Deep Venous Thrombosis in Elderly Patientswith Cerebral Hemorrhage

  • Shasha Zhang,
  • Bin Xu,
  • Wei Yan,
  • Jinyuan Chen

DOI
https://doi.org/10.3969/j.issn.1674-7593.2024.01.011
Journal volume & issue
Vol. 45, no. 1
pp. 59 – 63

Abstract

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Objective To investigate the risk factors of postoperative lower extremity deep venous thrombosis(DVT) in elderly patients with cerebral hemorrhage,and to construct a DVT risk assessment model. Methods A total of ninety five elderly patients with cerebral hemorrhage who underwent surgery in Jiangsu Provincial People's Hospital from July 2020 to January 2023 were selected as the study subjects and divided into DVT group(25 cases) and non-DVT group(70 cases) according to whether DVT occurred or not after surgery.The general data,preoperative and intraoperative related factors of the two groups were compared,and univariate analysis and multivariate logistic regression model analysis were used to screen the risk factors for the occurrence of DVT and construct a DVT risk assessment model. Results There were significant differences in age,smoking history,hypertension history,heart disease history,cerebral hemorrhage volume and operation time between the DVT group and the non-DVT group(P<0.05).Multivariate logistic regression model analysis showed that age≥70 years,smoking history,hypertension history,heart disease history,cerebral hemorrhage volume≥30 mL and operation time≥3 h were independent risk factors of postoperative DVT in elderly patients with cerebral hemorrhage(P<0.05).The DVT risk assessment model was constructed based on the regression coefficient,with a sensitivity of 88.0%,specificity of 85.7%,accuracy of 86.3%,and area under the curve of 0.938(95% CI:0.901~0.975). Conclusion A risk assessment model suitable for postoperative DVT in elderly patients with cerebral hemorrhage was constructed in this study,which has high accuracy and reliability and can provide the basis for the prevention and intervention of clinical DVT.

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