Derivation of a Simple Clinical Model to Categorize Patients Probability of Pulmonary Embolism: Increasing the Models Utility with the SimpliRED D-dimer

Philip S. Wells; David R. Anderson; Marc Rodger; Jeffrey S. Ginsberg; Clive Kearon; Michael Gent; Alexander G. G. Turpie; Janis Bormanis; Jeffrey Weitz; Michael Chamberlain; Dennis Bowie; David Barnes; Jack Hirsh

doi:10.1055/s-0037-1613830

Thrombosis and Haemostasis, Table of Contents

Thromb Haemost 2000; 83(03): 416-420
DOI: 10.1055/s-0037-1613830

Review Article

Schattauer GmbH

Derivation of a Simple Clinical Model to Categorize Patients Probability of Pulmonary Embolism: Increasing the Models Utility with the SimpliRED D-dimer

Philip S. Wells

¹Departments of Medicine, University of Ottawa, Ottawa, Canada, McMaster University, Hamilton, Canada, Dalhousie University, Halifax, Canada

,

David R. Anderson

¹Departments of Medicine, University of Ottawa, Ottawa, Canada, McMaster University, Hamilton, Canada, Dalhousie University, Halifax, Canada

,

Marc Rodger

¹Departments of Medicine, University of Ottawa, Ottawa, Canada, McMaster University, Hamilton, Canada, Dalhousie University, Halifax, Canada

,

Jeffrey S. Ginsberg

¹Departments of Medicine, University of Ottawa, Ottawa, Canada, McMaster University, Hamilton, Canada, Dalhousie University, Halifax, Canada

,

Clive Kearon

¹Departments of Medicine, University of Ottawa, Ottawa, Canada, McMaster University, Hamilton, Canada, Dalhousie University, Halifax, Canada

,

Michael Gent

¹Departments of Medicine, University of Ottawa, Ottawa, Canada, McMaster University, Hamilton, Canada, Dalhousie University, Halifax, Canada

,

Alexander G. G. Turpie

¹Departments of Medicine, University of Ottawa, Ottawa, Canada, McMaster University, Hamilton, Canada, Dalhousie University, Halifax, Canada

,

Janis Bormanis

¹Departments of Medicine, University of Ottawa, Ottawa, Canada, McMaster University, Hamilton, Canada, Dalhousie University, Halifax, Canada

,

Jeffrey Weitz

¹Departments of Medicine, University of Ottawa, Ottawa, Canada, McMaster University, Hamilton, Canada, Dalhousie University, Halifax, Canada

,

Michael Chamberlain

¹Departments of Medicine, University of Ottawa, Ottawa, Canada, McMaster University, Hamilton, Canada, Dalhousie University, Halifax, Canada

,

Dennis Bowie

¹Departments of Medicine, University of Ottawa, Ottawa, Canada, McMaster University, Hamilton, Canada, Dalhousie University, Halifax, Canada

,

David Barnes

¹Departments of Medicine, University of Ottawa, Ottawa, Canada, McMaster University, Hamilton, Canada, Dalhousie University, Halifax, Canada

,

Jack Hirsh

¹Departments of Medicine, University of Ottawa, Ottawa, Canada, McMaster University, Hamilton, Canada, Dalhousie University, Halifax, Canada

› Author Affiliations

Abstract

Summary

We have previously demonstrated that a clinical model can be safely used in a management strategy in patients with suspected pulmonary embolism (PE). We sought to simplify the clinical model and determine a scoring system, that when combined with D-dimer results, would safely exclude PE without the need for other tests, in a large proportion of patients. We used a randomly selected sample of 80% of the patients that participated in a prospective cohort study of patients with suspected PE to perform a logistic regression analysis on 40 clinical variables to create a simple clinical prediction rule. Cut points on the new rule were determined to create two scoring systems. In the first scoring system patients were classified as having low, moderate and high probability of PE with the proportions being similar to those determined in our original study. The second system was designed to create two categories, PE likely and unlikely. The goal in the latter was that PE unlikely patients with a negative D-dimer result would have PE in less than 2% of cases. The proportion of patients with PE in each category was determined overall and according to a positive or negative SimpliRED D-dimer result. After these determinations we applied the models to the remaining 20% of patients as a validation of the results. The following seven variables and assigned scores (in brackets) were included in the clinical prediction rule: Clinical symptoms of DVT (3.0), no alternative diagnosis (3.0), heart rate >100 (1.5), immobilization or surgery in the previous four weeks (1.5), previous DVT/PE (1.5), hemoptysis (1.0) and malignancy (1.0). Patients were considered low probability if the score was <2.0, moderate of the score was 2.0 to 6.0 and high if the score was over 6.0. Pulmonary embolism unlikely was assigned to patients with scores <4.0 and PE likely if the score was >4.0. 7.8% of patients with scores of less than or equal to 4 had PE but if the D-dimer was negative in these patients the rate of PE was only 2.2% (95% CI = 1.0% to 4.0%) in the derivation set and 1.7% in the validation set.

Importantly this combination occurred in 46% of our study patients. A score of <2.0 and a negative D-dimer results in a PE rate of 1.5% (95% CI = 0.4% to 3.7%) in the derivation set and 2.7% (95% CI = 0.3% to 9.0%) in the validation set and only occurred in 29% of patients. The combination of a score <4.0 by our simple clinical prediction rule and a negative SimpliRED D-Dimer result may safely exclude PE in a large proportion of patients with suspected PE.

Keywords

Pulmonary embolism - diagnosis - D-dimer - clinical assessment - regression analysis

Full Text

References

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