Trial reportBMC geriatrics2021
Individualized predictions of early isolated distal deep vein thrombosis in patients with acute ischemic stroke: a retrospective study.
Trial report in BMC geriatrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 27 citations in OpenAlex.
- Deep Vein Thrombosis Prevention in Acute Ischemic Stroke Patients with Lower Limb Paralysis: A Narrative Review.Journal of clinical medicine · 2026Review
- Machine learning-based model for predicting recanalization in isolated distal deep vein thrombosis and analysis of predictors.PloS one · 2026Article
- Machine learning-based prediction of in-hospital deep vein thrombosis in patients with acute ischemic stroke: a multicenter study.Frontiers in neurology · 2026Article
- Risk Assessment of Venous Thromboembolism in Neurocritical Patients: Construction and Validation of a Clinical Prediction Model.Mediators of inflammation · 2025Article
- Leveraging machine learning for enhanced and interpretable risk prediction of venous thromboembolism in acute ischemic stroke care.PloS one · 2025Article
- Machine learning-based prediction model of lower extremity deep vein thrombosis after stroke.Journal of thrombosis and thrombolysis · 2024Article
- Generation of a Predictive Clinical Model for Isolated Distal Deep Vein Thrombosis (ICMVT) Detection.Medical science monitor : international medical journal of experimental and clinical research · 2023Article
- The interaction effect of transfusion history and previous stroke history on the risk of venous thromboembolism in stroke patients: a prospective cohort study.Thrombosis journal · 2023Article
- Nomogram to predict hemorrhagic transformation for acute ischemic stroke in Western China: a retrospective analysis.BMC neurology · 2022Article
- Risk factors for relapse and nomogram for relapse probability prediction in patients with minor ischemic stroke.World journal of clinical cases · 2021Article
- A Machine Learning-Based Prognostic Model for Lower Extremity Deep Vein Thrombosis Following Acute Stroke.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/HemostasisArticle
- Isolated distal deep vein thrombosis: Diagnosis and management.Science progressReview
- A Nomogram for Individualized Prediction of Calf Muscular Vein Thrombosis in Stroke Patients During Rehabilitation: A Retrospective Study.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/HemostasisArticle
- Risk factors and nomogram prediction model for isolated distal deep vein thrombosis after endovascular treatment in acute ischemic stroke patients.Frontiers in neurologyArticle
Corrections and comments
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Authors and funding
12 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundAlthough isolated distal deep vein thrombosis (IDDVT) is a clinical complication for acute ischemic stroke (AIS) patients, very few clinicians value it and few methods can predict early IDDVT. This study aimed to establish and validate an individualized predictive nomogram for the risk of early IDDVT in AIS patients.
methodsThis study enrolled 647 consecutive AIS patients who were randomly divided into a training cohort (n = 431) and a validation cohort (n = 216). Based on logistic analyses in training cohort, a nomogram was constructed to predict early IDDVT. The nomogram was then validated using area under the receiver operating characteristic curve (AUROC) and calibration plots.
resultsThe multivariate logistic regression analysis revealed that age, gender, lower limb paralysis, current pneumonia, atrial fibrillation and malignant tumor were independent risk factors of early IDDVT; these variables were integrated to construct the nomogram. Calibration plots revealed acceptable agreement between the predicted and actual IDDVT probabilities in both the training and validation cohorts. The nomogram had AUROC values of 0.767 (95% CI: 0.742-0.806) and 0.820 (95% CI: 0.762-0.869) in the training and validation cohorts, respectively. Additionally, in the validation cohort, the AUROC of the nomogram was higher than those of the other scores for predicting IDDVT.
conclusionsThe present nomogram provides clinicians with a novel and easy-to-use tool for the prediction of the individualized risk of IDDVT in the early stages of AIS, which would be helpful to initiate imaging examination and interventions timely.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.