Predictive and associative models to identify hospitalized medical patients at risk for VTE.
Publication/Presentation Date
9-1-2011
Abstract
BACKGROUND: Acutely ill hospitalized medical patients are at risk for VTE. We assessed the incidence of VTE in the observational International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) study and derived VTE risk assessment scores at admission and associative VTE scores during hospitalization.
METHODS: Data from 15,156 medical patients were analyzed to determine the cumulative incidence of clinically observed VTE over 3 months after admission. Multiple regression analysis identified factors associated with VTE risk.
RESULTS: Of the 184 patients who developed symptomatic VTE, 76 had pulmonary embolism, and 67 had lower-extremity DVT. Cumulative VTE incidence was 1.0%; 45% of events occurred after discharge. Factors independently associated with VTE were previous VTE, known thrombophilia, cancer, age > 60 years, lower-limb paralysis, immobilization ≥ 7 days, and admission to an ICU or coronary care unit (first four were available at admission). Points were assigned to each factor identified to give a total risk score for each patient. At admission, 67% of patients had a score ≥ 1. During hospitalization, 31% had a score ≥ 2; for a score of 2 or 3, observed VTE risk was 1.5% vs 5.7% for a score ≥ 4. Observed and predicted rates were similar for both models (C statistic, 0.65 and 0.69, respectively). During hospitalization, a score ≥ 2 was associated with higher overall and VTE-related mortality.
CONCLUSIONS: Weighted VTE risk scores derived from four clinical risk factors at hospital admission can predict VTE risk in acutely ill hospitalized medical patients. Scores derived from seven clinical factors during hospitalization may help us to further understand symptomatic VTE risk. These scores require external validation.
Volume
140
Issue
3
First Page
706
Last Page
714
ISSN
1931-3543
Published In/Presented At
Spyropoulos, A. C., Anderson, F. A., Jr, FitzGerald, G., Decousus, H., Pini, M., Chong, B. H., Zotz, R. B., Bergmann, J. F., Tapson, V., Froehlich, J. B., Monreal, M., Merli, G. J., Pavanello, R., Turpie, A. G. G., Nakamura, M., Piovella, F., Kakkar, A. K., Spencer, F. A., & IMPROVE Investigators (2011). Predictive and associative models to identify hospitalized medical patients at risk for VTE. Chest, 140(3), 706–714. https://doi.org/10.1378/chest.10-1944
Disciplines
Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods
PubMedID
21436241
Department(s)
Administration and Leadership
Document Type
Article