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  • Title: Clinical prediction of pulmonary embolism in respiratory emergencies.
    Author: Tsimogianni AM, Rovina N, Porfyridis I, Nikoloutsou I, Roussos C, Zakynthinos SG, Stathopoulos GT.
    Journal: Thromb Res; 2011 May; 127(5):411-7. PubMed ID: 21396683.
    Abstract:
    INTRODUCTION: The initial management of suspected pulmonary embolism (PE) is commonly done in respiratory departments, but is based on clinical prediction rules developed in other settings. OBJECTIVE: To determine the accuracy of established prediction rules for PE in patients with respiratory emergencies. DESIGN: A prospective study MATERIALS AND METHODS: Patients presenting to respiratory emergency department with acute symptoms and signs suggestive of PE (n=183) and subsequently admitted to hospital were prospectively enrolled. Wells' rule, original and revised Geneva scores, their components separately, and other common clinical parameters were recorded during admission. PE was diagnosed by perfusion lung scanning, computed tomographic pulmonary angiography, lower limb venous ultrasonography, magnetic resonance pulmonary angiography, and/or pulmonary angiography. RESULTS: PE was confirmed in 52 and ruled out in 131 patients. Tachycardia, atelectasis, elevated hemidiaphragm, clinical signs of deep-venous thrombosis, physician perception that PE is the likeliest diagnosis, previous thromboembolism, chest pain, and absence of chronic obstructive pulmonary disease or cough were associated with the presence of PE. These significant parameters could be combined for accurate pre-test PE prediction, with a newly devised combinatorial tool exhibiting the highest area under curve [0.92 (95% CI: 0.87-0.97)], followed by Wells' rule [0.86 (95% CI 0.79-0.92)], the revised Geneva score [0.83 (95% CI 0.77-0.90)], and the original Geneva score [0.75 (95% CI 0.68-0.83)]. CONCLUSION: Wells' rule and the revised Geneva score are more useful in diagnosing PE in respiratory emergencies. A newly devised prediction tool can be of even greater accuracy in this patient population.
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