ArticleClinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
Nomogram Prediction for Lower Extremity Deep Vein Thrombosis in Acute Ischemic Stroke Patients Receiving Thrombolytic Therapy.
Article in Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 5 citations in OpenAlex.
- Risk factors and intervention strategies for lower extremity deep vein thrombosis after intravenous thrombolysis for acute ischemic stroke.Frontiers in cardiovascular medicine · 2026Article
- Machine learning-based prediction of in-hospital deep vein thrombosis in patients with acute ischemic stroke: a multicenter study.Frontiers in neurology · 2026Article
- Developing a predictive model for lower extremity deep vein thrombosis in acute ischemic stroke using a nomogram.Frontiers in neurology · 2025Article
- Risk factors and predictive nomogram for multi-organ failure in patients with acute kidney failure combined with severe sepsis.American journal of translational research · 2025Article
- Leveraging machine learning for enhanced and interpretable risk prediction of venous thromboembolism in acute ischemic stroke care.PloS one · 2025Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
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Abstract
This study developed and evaluated a tailored nomogram to predict the potential occurrence of early lower extremity deep vein thrombosis (LDVT) in patients receiving thrombolytic therapy. We performed several logistic analyses on the training cohort and created a corresponding nomogram to forecast early LDVT. The classification accuracy and the accuracy of predicted probabilities of the multiple logistic regression model were evaluated using area under the curve (AUC) and the calibration graph method. According to the multivariate logistic regression model homocysteine, previous history of hypertension and atrial fibrillation, indirect bilirubin, age, and sex was identified as independent determinants of early LDVT. The nomogram was constructed using these variables. The calibration plots showed a good agreement between the predicted and observed LDVT possibilities in the training and validation cohorts with AUCs being 0.833 (95% CI: 0.774-0.892) and 0.907 (95% CI: 0.801-1.000), respectively. Our nomogram offers clinicians a tool for predicting the individual risk of LDVT in the early stage of acute ischemic stroke in patients receiving thrombolytic therapy, which could lead to early intervention.
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