ArticleClinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
Development of a Risk Assessment Tool for Venous Thromboembolism among Hospitalized Patients in the ICU.
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 3 papers, 1 of them a synthesis that pooled it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Risk factors of venous thromboembolism in ICU patients: a systematic review and meta-analysis.Annals of medicine · 2026Pooled it
- The Caprini score for venous thromboembolism risk assessment: A scoping review of applications, validation, and future directions.Journal of vascular surgery. Venous and lymphatic disorders · 2026Article
- Machine Learning-Based Early Prediction of Lower Extremity Deep Vein Thrombosis in the ICU: A Multicenter Study.Risk management and healthcare policy · 2026Article
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8 authors.
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Abstract
backgroundICU patients have a high incidence of VTE. The American College of Chest Physicians antithrombotic practice guidelines recommend assessing the risk of VTE in all ICU patients. Although several VTE risk assessment tools exist to evaluate the risk factors among hospitalized patients, there is no validated tool specifically for assessing the risk of VTE in ICU patients.
methodsA retrospective corhort study was conducted between June 2018 and October 2022. We obtained data from the electronic medical records of patients with a variety of diagnoses admitted to a mixed ICU. Multivariable logistic regression analysis was used to evaluate the independent risk factors of VTE. Receiver operating characteristic (ROC) curves were used to analyse the predictive accuracy of different tools.
resultsA total of 566 patients were included, and VTE occurred in 89 patients (15.7%), 62.9% was asymptomatic VTE. A prediction model (the ICU-VTE prediction model) was derived from the independent risk factors identified using multivariate analysis. The ICU-VTE prediction model included eight independent risk factors: history of VTE (3 points), immobilization ≥4 days (3 points), multiple trauma (3 points), age ≥70 years (2 points), platelet count >250 × 10
conclusionsWe identified eight independent risk factors for acquired VTE among hospitalized patients in the ICU, deriving a new ICU-VTE risk assessment model. The model aims to predict asymptomatic VTE in ICU patients. The new model has higher predictive accuracy than the current tools. A prospective study is required for external validation of the tool and risk stratification in ICU patients.
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