European Heart Journal Advance Access originally published online on April 7, 2006
European Heart Journal 2006 27(11):1384-1385; doi:10.1093/eurheartj/ehi866
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Risk assessment in acute pulmonary embolism: reply
Service de Médecine Interne
BH10-622, Centre Hospitalier Universitaire Vaudois
1011 Lausanne
Switzerland
Tel: +41 21 314 04 81
Fax: +41 21 314 08 71
E-mail address: drahomir.aujesky{at}chuv.ch
Kostrubiec and colleagues are concerned that our 11-variable prognostic model for pulmonary embolism (PE) may be too complex to be applied in clinical practice and that some of the variables of the model may be difficult to assess. While we agree that the application of our model probably necessitates the help of a written reminder, the model consists of 11 easily available demographic characteristics and history and physical examination findings, without the need for laboratory or radiographic tests.1,2 This should greatly facilitate the practical applicability of the model. While the reproducibility of our model was not yet tested in an interobserver agreement study, all prognostic factors represent explicit, dichotomous variables that can be easily obtained at the patient's bedside. These factors include the patient's age, sex, pulse, blood pressure, respiratory rate, temperature, arterial oxygen saturation, an altered mental status (defined as the presence of disorientation, lethargy, stupor, or coma), and a known history of cancer, heart failure, or any chronic lung disease.1,2 The severity of heart failure, as implied by Kostrubiec, does not play a role in our model.
Kostrubiec and colleagues criticize that the creatinine level, a known prognostic factor for PE, is not part of our model. To facilitate its applicability, we derived the model using only clinical factors, without the inclusion of laboratory parameters. However, we also assessed several laboratory variables as potential predictors in the logistic regression model.1 In this more complex model, a blood urea nitrogen value of 
11 mmol/L (but not a creatinine >133 µmol/L) was independently associated with mortality. Although the more complex model including laboratory variables achieved a slightly higher discriminatory power for mortality, its overall prognostic performance was not superior to the simpler model.1
Our model is most useful in identifying low-risk patients with PE who are potential candidates for outpatient treatment with low-molecular weight heparins. Patients with the highest risk based on our model (risk class V) had a 30-day mortality between 10–25%, resulting in positive predictive values (PPVs) for mortality of 11–14%.1,2 While these PPVs are too low to accurately identify high-risk patients with PE, the PPVs of cardiac biomarkers and echocardiography are similarly low (6–44 and 10–41%, respectively) and offer no real advantage over our model.3–5
Cardiac biomarkers such as troponins and brain natriuretic peptides (BNPs) have a high negative predictive value (>93%) for mortality in patients with PE.5 However, the ability of cardiac biomarkers to identify low-risk patients is currently unclear because prognostic studies for PE using troponins or BNPs with or without echocardiography are limited by relatively small sample sizes from single hospitals, inconsistent results, and different testing methods (e.g. troponin I or T, BNP or NT-proBNP) and cut-off values to define abnormal results.4,6 Moreover, echocardiography may not be available 24 h a day in smaller community hospitals. Thus, although our 11-variable model is more complex than a single laboratory parameter, its usefulness to identify low-risk patients with PE has been proved in almost 16 000 patients from 305 European and US hospitals.1,2
References
- Aujesky D, Obrosky DS, Stone RA, Auble TE, Perrier A, Cornuz J, Roy PM, Fine MJ. (2005) Derivation and validation of a prognostic model for pulmonary embolism. Am J Respir Crit Care Med 172:1041–1046.
[Abstract/Free Full Text] - Aujesky D, Roy PM, Le Manach CP, Verschuren F, Meyer G, Obrosky DS, Stone RA, Cornuz J, Fine MJ. (2006) Validation of a model to predict adverse outcomes in patients with pulmonary embolism. Eur Heart J 27:476–481.
[Abstract/Free Full Text] - ten Wolde M, Sohne M, Quak E, Mac Gillavry MR, Buller HR. (2004) Prognostic value of echocardiographically assessed right ventricular dysfunction in patients with pulmonary embolism. Arch Intern Med 164:1685–1689.
[Abstract/Free Full Text] - Gibson NS, Sohne M, Buller HR. (2005) Prognostic value of echocardiography and spiral computed tomography in patients with pulmonary embolism. Curr Opin Pulm Med 11:380–384.[CrossRef][Web of Science][Medline]
- Sohne M, ten Wolde M, Buller HR. (2004) Biomarkers in pulmonary embolism. Curr Opin Cardiol 19:558–562.[CrossRef][Web of Science][Medline]
- Kruger S, Merx MW, Graf J. (2003) Utility of brain natriuretic peptide to predict right ventricular dysfunction and clinical outcome in patients with acute pulmonary embolism. Circulation 108:e94–e95.
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