A composite risk assessment model for venous thromboembolism
Using a composite of 102 risk factors from all available VTE RAMs, we improved VTE prediction in a large, national cohort of >1 million general hospital admissions. However, neither model has a sensitivity or PPV that permits it to be a reliable predictor of VTE. We demonstrate the limits of currently available VTE risk prediction tools; no available RAM is ready for widespread use in the general hospital population.
Authors
- Minerva Mayorga‐Carlin (ORCID: https://orcid.org/0000-0003-2125-642X)
- John D. Sorkin (ORCID: https://orcid.org/0000-0003-2496-0965)
- Brian R. Englum
- Tariq Siddiqui (ORCID: https://orcid.org/0000-0001-8818-6388)
- Hilary Hayssen
- Brajesh K. Lal (ORCID: https://orcid.org/0000-0001-6724-8201)
- Shalini Sahoo
- Yelena Yesha
- Georges Jreij (ORCID: https://orcid.org/0009-0003-7539-9714)
- Phuong L. Nguyen
- Mary Sixian Lin
Institutions
- University of Maryland, Baltimore (US)
- University of Maryland Medical Center (US)
- University of Miami (US)
- Baltimore VA Medical Center (US)
Publication Details
- Journal
- Journal of Vascular Surgery Venous and Lymphatic Disorders
- Published
- 2024-09-19
- DOI
- https://doi.org/10.1016/j.jvsv.2024.101968
- Citations
- 6
- Primary Topic
- Venous Thromboembolism Diagnosis and Management
- Type
- article
- Field-Weighted Citation Impact
- 3.30
Funders
- National Institutes of Health