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A Multicenter MRI Protocol for the Evaluation and Quantification of Deep Vein Thrombosis
Published on: June 2, 2015
Development and validation of a predictive risk model for post-stroke deep vein thrombosis
1Department of Neurology, Tongde Hospital of Zhejiang Province, Hangzhou, Zhejiang, China.
Biomolecules & Biomedicine
|June 14, 2026
Summary
A new nomogram helps predict deep vein thrombosis (DVT) risk after acute ischemic stroke (AIS). This tool uses patient factors like age and fibrinogen to identify high-risk individuals early, improving patient management.
Area of Science:
- Medical Research
- Clinical Prediction Models
- Vascular Medicine
Background:
- Deep vein thrombosis (DVT) is a frequent and serious complication post-acute ischemic stroke (AIS).
- Early identification of DVT risk is challenging due to asymptomatic presentation and lack of specific predictive tools for AIS patients.
Purpose of the Study:
- To develop and validate a predictive nomogram for forecasting DVT risk in AIS patients.
- To identify key baseline patient characteristics associated with post-stroke DVT development.
Main Methods:
- Retrospective analysis of 848 AIS patients, with 79 developing DVT.
- Utilized Least Absolute Shrinkage and Selection Operator (LASSO) and multivariable logistic regression for predictor identification.
- Constructed a nomogram based on identified predictors and validated using bootstrapping and decision curve analysis.
Main Results:
- Five independent predictors for DVT risk were identified: age, fibrinogen, D-dimer, platelet count, and sex.
- The nomogram demonstrated strong predictive performance with an AUC of 0.809 (0.800 after validation).
- The model showed excellent calibration and clinical utility across a wide probability range.
Conclusions:
- An exploratory nomogram was successfully developed for early DVT risk estimation in AIS patients.
- The nomogram provides a valuable tool for risk stratification and clinical decision-making.
- Further prospective validation is warranted to confirm its clinical utility.
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