We have located links that may give you full text access.
[Validity of Padua risk assessment scale for assessing the risk of deep venous thrombosis in hospitalized patients].
To analyze the clinical features of deep venous thrombosis(DVT) in hospitalized patients and evaluate the effectiveness of Padua risk assessment model.The clinical data of DVT patients were retrospectively analyzed in Beijing Shijitan Hospital from April 1 2017 to June 30, 2017.Padua risk assessment scale was used to evaluate the risk score of DVT in the departments of internal medicine and surgery. Effectiveness of predicting DVT was analyzed by receiver operating characteristic curve (ROC).Logistic regression analysis was used to evaluate the related factors of DVT.In DVT group, age ( OR= 0.96),acute infection( OR= 8.23),prothrombin time( OR= 0.76),D dimer( OR= 1.00),erythrocyte sedimentation rate( OR= 1.02) and platelet count( OR= 1.01) were significantly associated with thrombosis(all P< 0.05).The specificity of Padua model to predict DVT in internal medical patients was better than the sensitivity(80.7% vs. 50%, P< 0.05).Surgical patients reported similar findings with specificity to sensitivity of 87.5% vs. 67.5%( P< 0.05).The area under curve of ROC in internal medical patients was more than that in surgical patients[0.62 (95% CI 0.59-0.67) vs.0.61(95% CI 0.56-0.66), P< 0.05].Padua model is more specific than sensitive to predict DVT in hospitalized patients.It has better predictive value of DVT in internal medical patients than surgical patients.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app