Thromb Haemost 2012; 108(06): 1072-1076
DOI: 10.1160/TH12-07-0508
Clinical Focus
Schattauer GmbH

The use of weighted and scored risk assessment models for venous thromboembolism

Alex C. Spyropoulos
1   James P. Wilmot Cancer Center and Department of Medicine, University of Rochester Medical Center, Rochester, New York, USA;
,
Thomas McGinn
2   North Shore/LIJ Health System, Department of Medicine, New York, New York, USA
,
Alok A. Khorana
1   James P. Wilmot Cancer Center and Department of Medicine, University of Rochester Medical Center, Rochester, New York, USA;
› Author Affiliations
Further Information

Publication History

Received: 20 July 2012

Accepted after major revision:12 September 2012

Publication Date:
30 November 2017 (online)

Summary

Formalised risk assessment models (RAMs) for venous thromboembolism (VTE) using weighted and scored variables have only recently been widely incorporated into international antithrombotic guidelines.Scored and weighted VTE RAMs have advantages over a simplified group-specific VTE risk approach, with the potential to allow more tailored strategies for thromboprophylaxis and an improved estimation of the risk/benefit profile for a particular patient. The derivation of VTE RAMs should be based on variables that are a priori defined or identified in a univariate analysis and the predictive capability of each variable should be rigorously assessed for both clinical and statistical significance and internal consistency and completeness. The assessment of the RAM should include the goodness of fit of the model and construction of a prognostic index score. Any VTE RAM which has been derived must undergo validation of that model before it can be used in clinical practice. Validation of the model should be performed in a “deliberate”prospective fashion across several diverse clinical sites using pre-defined criteria using basic standards for performing model validation. We discuss the basic concepts in the derivation of recent scored and weighted VTE RAMs in hospitalised surgical and medical patients and cancer outpatients, the mechanisms for accurate external validation of the models, and implications for their use in clinical practice.

 
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