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Derivation and Validation of a Simple Model to Identify Venous Thromboembolism Risk in Medical Patients - 29/09/11

Doi : 10.1016/j.amjmed.2011.06.004 
Scott C. Woller, MD a, b, , Scott M. Stevens, MD a, b, Jason P. Jones, PhD c, d, James F. Lloyd, BS c, R. Scott Evans, PhD c, e, Valerie T. Aston, RRT a, C. Gregory Elliott, MD a, b
a Intermountain Medical Center, Murray, Utah 
b University of Utah School of Medicine, Salt Lake City 
c Intermountain Healthcare Medical Informatics, Murray, Utah 
d Kaiser Permanente Southern California, Pasadena, California 
e Department of Biomedical Informatics, University of Utah, Salt Lake City 

Requests for reprints should be addressed to Scott C. Woller, MD, Intermountain Medical Center, Eccles Outpatient Care Center, Edwards Internal Medicine Clinic, Suite 300, PO Box 577000, Murray, UT 84157-7000

Abstract

Background

Fewer than half of eligible hospitalized medical patients receive appropriate venous thromboembolism (VTE) prophylaxis. One reason for this low rate is the complexity of existing risk assessment models. A simple set of easily identifiable risk factors that are highly predictive of VTE among hospitalized medical patients may enhance appropriate thromboprophylaxis.

Methods

Electronic medical record interrogation was performed to identify medical admissions from January 1, 2000-December 31, 2007 (n=143,000), and those patients with objectively confirmed VTE during hospitalization or within 90 days following discharge. Putative risk factors most predictive of VTE were identified, and a risk assessment model (RAM) was derived; 46,000 medicine admissions from January 1, 2008-December 31, 2009 served as a validation cohort to test the predictive ability of the RAM. The newly derived RAM was compared with a published VTE assessment tool (Kucher Score).

Results

Four risk factors: previous VTE; an order for bed rest; peripherally inserted central venous catheterization line; and a cancer diagnosis, were the minimal set most predictive of hospital-associated VTE (area under the receiver operating characteristic curve [AUC]=0.874; 95% confidence interval [CI], 0.869-0.880). These risk factors upon validation in a separate population (validation cohort) retained an AUC=0.843; 95% CI, 0.833-0.852. The ability of the 4-element RAM to identify patients at risk of developing VTE within 90 days was superior to the Kucher Score.

Conclusions

The 4-element RAM identified in this study may be used to identify patients at risk for VTE and improve rates of thromboprophylaxis. This simple and accurate RAM is an alternative to more complicated published VTE risk assessment tools that currently exist.

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Keywords : Deep vein thrombosis, Pulmonary embolism, RAM, Risk assessment model, Risk score, Venous thromboembolism


Esquema


 Funding: This research was supported in part by a grant provided by the Deseret Foundation.
 Conflict of Interest: None.
 Authorship: All authors report full access to all data in the study, take responsibility for the integrity of the data accuracy and analysis, and participated in writing and revision of the manuscript.


© 2011  Elsevier Inc. Reservados todos los derechos.
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Vol 124 - N° 10

P. 947 - octobre 2011 Regresar al número
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