Predicting 30-Day Venous Thromboembolism Following Total Joint Arthroplasty: Adjusting for Trends in Annual Length of Stay
This study revealed declining VTE rates strongly correlated to decreasing postoperative LOS and identified patient and surgery-specific factors associated with VTE risk. Development of more accurate machine learning models for VTE prediction may improve risk stratification, prevention, and monitoring for arthroplasty patients.
Authors
- Aazad Abbas (ORCID: https://orcid.org/0000-0001-7414-1701)
- Alexander S. McLawhorn (ORCID: https://orcid.org/0000-0001-7841-5095)
- Bheeshma Ravi (ORCID: https://orcid.org/0000-0003-1829-6885)
- Johnathan R. Lex (ORCID: https://orcid.org/0000-0002-8171-5344)
- Robert Koucheki (ORCID: https://orcid.org/0000-0002-6156-6660)
- Jesse Wolfstadt
Institutions
- Hospital for Special Surgery (US)
- Mount Sinai Hospital (CA)
- Sunnybrook Health Science Centre (CA)
- University of Toronto (CA)
- Health Sciences Centre (CA)
Publication Details
- Journal
- Arthroplasty Today
- Published
- 2024-10-16
- DOI
- https://doi.org/10.1016/j.artd.2024.101491
- Citations
- 4
- Primary Topic
- Venous Thromboembolism Diagnosis and Management
- Type
- article
- Field-Weighted Citation Impact
- 2.20