摘要
Abstract
Objective To analyze the risk factors for the occurrence of deep venous thrombosis(DVT)in stroke patients and construct a prediction model.Methods A total of 100 stroke patients who were hospitalized in Taizhou Rehabilitation Hospital,Taizhou Enze Medical Center(Group)from October 2024 to October 2025 were selected.They were divided into DVT group(n=22)and non-DVT group(n=78)based on whether they developed lower extremity DVT.Univariate and multivariate Logistic regression analyses were conducted to identify the risk factors for lower extremity DVT in stroke patients,and a predictive model was constructed.The goodness of fit and efficacy of the model were verified through the Hosmer-Lemeshow test and receiver operating characteristic(ROC)curve.Results The age of patients in DVT group was significantly older than that in non-DVT group,the proportions of those who drank,smoked,and had bed rest for≥3 days were also significantly higher than those in non-DVT group,prothrombin time(PT)and activated partial thromboplastin time(APTT)were significantly shorter than those in non-DVT group,mean platelet volume(MPV)was significantly lower than that in non-DVT group,and D-dimer(D-D)was significantly higher than that in non-DVT group(P<0.05).Multivariate Logistic regression analysis revealed that advanced age,prolonged bed rest,short PT,short APTT,low MPV,and high D-D were all risk factors for the occurrence of lower extremity DVT in stroke patients(P<0.05).The prediction model constructed based on the above analysis results had a good fit(P>0.05).The area under ROC curve was 0.828,indicating good predictive performance(P<0.001).Conclusion Advanced age,prolonged bed rest,short PT,short APTT,low MPV,and high D-D are all risk factors for lower extremity DVT in stroke patients.The prediction model constructed based on these factors is helpful in identifying high-risk patients and providing a reference for early prevention.关键词
脑卒中/深静脉血栓/危险因素/预测模型Key words
Stroke/Deep venous thrombosis/Risk factor/Predictive model分类
医药卫生
