Literature DB >> 10744147

Derivation of a simple clinical model to categorize patients probability of pulmonary embolism: increasing the models utility with the SimpliRED D-dimer.

P S Wells1, D R Anderson, M Rodger, J S Ginsberg, C Kearon, M Gent, A G Turpie, J Bormanis, J Weitz, M Chamberlain, D Bowie, D Barnes, J Hirsh.   

Abstract

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 < or =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 < or =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.

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Year:  2000        PMID: 10744147

Source DB:  PubMed          Journal:  Thromb Haemost        ISSN: 0340-6245            Impact factor:   5.249


  252 in total

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Authors:  Arjun K Venkatesh; Jeffrey A Kline; D Mark Courtney; Carlos A Camargo; Michael C Plewa; Kristen E Nordenholz; Christopher L Moore; Peter B Richman; Howard A Smithline; Daren M Beam; Christopher Kabrhel
Journal:  Arch Intern Med       Date:  2012-07-09

2.  Pulmonary embolism: investigation of the clinically assessed intermediate risk subgroup.

Authors:  D J Warren; S Matthews
Journal:  Br J Radiol       Date:  2011-09-21       Impact factor: 3.039

3.  British Thoracic Society guidelines for the management of suspected acute pulmonary embolism.

Authors: 
Journal:  Thorax       Date:  2003-06       Impact factor: 9.139

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Journal:  Int J Cardiovasc Imaging       Date:  2012-01-08       Impact factor: 2.357

5.  84-year-old woman with chest pain.

Authors:  Evan L Hardegree; Malcolm R Bell
Journal:  Mayo Clin Proc       Date:  2012-07       Impact factor: 7.616

6.  Relation between pulmonary embolus volume quantified by multidetector computed tomography and clinical status and outcome for patients with acute pulmonary embolism.

Authors:  Kei Nakada; Takemichi Okada; Hisato Osada; Norinari Honda
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7.  Clinical decision making: an introduction.

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Journal:  Intern Emerg Med       Date:  2010-11-13       Impact factor: 3.397

Review 8.  Acute pulmonary embolism. Part 1: epidemiology and diagnosis.

Authors:  Renée A Douma; Pieter W Kamphuisen; Harry R Büller
Journal:  Nat Rev Cardiol       Date:  2010-07-20       Impact factor: 32.419

9.  The essence of the Japan Radiological Society/Japanese College of Radiology Imaging Guideline.

Authors:  Yasuyuki Yamashita; Sadayuki Murayama; Masahiro Okada; Yoshiyuki Watanabe; Masako Kataoka; Yasushi Kaji; Keiko Imamura; Yasuo Takehara; Hiromitsu Hayashi; Kazuko Ohno; Kazuo Awai; Toshinori Hirai; Kazuyuki Kojima; Shuji Sakai; Naofumi Matsunaga; Takamichi Murakami; Kengo Yoshimitsu; Toshifumi Gabata; Kenji Matsuzaki; Eriko Tohno; Yasuhiro Kawahara; Takeo Nakayama; Shuichi Monzawa; Satoru Takahashi
Journal:  Jpn J Radiol       Date:  2016-01       Impact factor: 2.374

10.  American Society of Hematology 2018 guidelines for management of venous thromboembolism: diagnosis of venous thromboembolism.

Authors:  Wendy Lim; Grégoire Le Gal; Shannon M Bates; Marc Righini; Linda B Haramati; Eddy Lang; Jeffrey A Kline; Sonja Chasteen; Marcia Snyder; Payal Patel; Meha Bhatt; Parth Patel; Cody Braun; Housne Begum; Wojtek Wiercioch; Holger J Schünemann; Reem A Mustafa
Journal:  Blood Adv       Date:  2018-11-27
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