Comparison of 3 clinical models for predicting the probability of pulmonary embolism

Two clinical models have been described to predict the probability of pulmonary embolism: the Canadian (or Wells) model, and the Geneva model. A third model has been developed recently at our institution (the Pisa model). We compared the performance of the 3 models in 215 consecutive patients with suspected pulmonary embolism. The clinical probability predicted by the models was categorized as low, intermediate, or high. In all patients, pulmonary angiography was used as the reference diagnostic standard. In patients with pulmonary embolism, the extent of pulmonary embolization was assessed on the lung scan as an index of disease severity. The prevalence of pulmonary embolism was 43.3%, and the median extent of pulmonary embolization at diagnosis was 39.8% (range, 4.5%-75.3%). The proportions of patients categorized as having low, intermediate, or high probability were, respectively: 12%, 60%, and 28%, for the Geneva model; 30%, 55%, and 15%, for the Wells model; 37%, 37%, and 26% for the Pisa model. The frequencies of pulmonary embolism in the low, intermediate, and high probability categories were, respectively: 50%, 39%, and 49% for the Geneva model; 12%, 54%, and 64% for the Wells model; 5%, 42%, and 98% for the Pisa model. Among patients with pulmonary embolism, there was a strong, positive relation between clinical probability predicted by the Pisa model and the extent of pulmonary embolization. The Pisa model proved more accurate than the 2 other models. It may be useful to physicians in defining precisely the pretest probability of pulmonary embolism.