<b>A Simplified Clinical Model to Predict Pulmonary Embolism in Patients With Acute Dyspnea</b>

Abstract

SUMMARYThe objective of the present study was to develop a simple clinical model for predicting pulmonary embolism (PE) in patients with acute dyspnea in the emergency room.Patients and measurements: We enrolled 56 patients diagnosed with PE, and 92 consecutive patients without PE, all of whom presented with acute dyspnea in the emergency room. Primary emergency-room physicians assessed the initial evaluation and interpretation of various laboratory findings. Some significantly independent predictors of PE were identified and integrated into a clinical model of pretest probability: low (< 30%), intermediate (≥ 30%, ≤ 70%), and high (> 70%). After setting up the model, another 40 patients (16 with PE, 24 without PE) were tested using the pretest model.Clinical variables associated with an increased likelihood of PE were being female and having unilateral low-leg edema, a high alveolar-arterial oxygen gradient, a clear chest x-ray, and electrocardiographic findings of right ventricular strain. Variables associated with a decreased likelihood of PE were cough, chest tightness, and unclear breath sounds. Our clinical model predicted that 95% of patients with PE had a high or low probability of PE. The positive predictive value for high probability was 94.1% and the negative predictive value for low probability was 94.4%. In the tested group, the positive predictive value for high probability was 92.9%. The negative predictive value for low probability was 91.3%.This simple and easily available prediction model was useful for estimating the pretest probability of PE in patients with acute dyspnea. (Int Heart J 2006; 47: 259-271) Key words: Pulmonary embolism, Acute dyspnea, Pretest probability PULMONARY embolism (PE) can lead to early death or serious morbidity. [1][2][3][4][5] Early diagnosis and appropriate management can decrease the mortality and morbidity.6-12) Therefore, a simple and readily available clinical indicator for primary physicians to accurately predict the probability of PE will be beneficial and is necessary. Previous 13-16) structured clinical models for early pretests of the proba- [13][14][15][16] placed relatively large proportions of patients in the intermediate probability category, which was of limited utility to both physicians and patients. Furthermore, previous models used suspected PE instead of specific symptoms as the initial inclusion criterion for patient recruitment. [13][14][15][16] This criterion, however, lacked a clear definition because, in part, different physicians had different perceptions of suspected PE. These models, therefore, led to heterogeneous populations predicted to have PE, which undoubtedly led to variable pretest probabilities [13][14][15][16] and the low accuracy of these models. 14-16) Consequently, these models were of limited value in clinical practice.The purpose of this study was to determine the efficacy of a clinical model integrating simple and readily available clinical parameters, viz. symptoms, physical findings, and the results of chest x-ray, e...

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