Impact of reliance on CT pulmonary angiography on diagnosis of pulmonary embolism: A Bayesian analysis

BACKGROUND: Spiral computed tomographic pulmonary angiography (CTPA) has become the primary test used to investigate suspected pulmonary embolism (PE) at many institutions, despite uncertainty regarding its sensitivity and specificity. Although CTPA-based diagnostic algorithms focus on minimizing the false-negative rate, we hypothesized that increasing use of CTPA also might lead to false-positive diagnoses. OBJECTIVE: Determine the frequency of possible false-positive diagnoses of PE when CTPA is the primary diagnostic test. DESIGN: Retrospective cohort study. SETTING: Two academic teaching hospitals. PARTICIPANTS: 322 patients with suspected PE evaluated with CTPA. MEASUREMENTS: We used a validated prediction rule to determine the pretest probability of PE in each patient. We combined these pretest probabilities with published estimates of CTPA test characteristics to generate expected posttest probabilities of PE. We compared these posttest probabilities to actual treatment decisions to determine the rate of false-positive diagnoses of PE. RESULTS: Among 322 patients investigated for PE, 37 (12%) had high pretest probability, 101 (32%) moderate, and 184 (57%) low. CT scans were interpreted as positive for PE in 57 patients (17.8%). Regardless of the pretest probability of PE, 96.5% of patients with a positive CTPA were treated with anticoagulants. Even under an optimistic assumption of CTPA test characteristics, as many as 25.4% of these patients may have been treated unnecessarily as a result of a false-positive diagnosis. Most of these patients had a low pretest probability of PE. CONCLUSIONS: Failure to utilize Bayesian reasoning when interpreting GTPA may lead to false-positive diagnoses of pulmonary embolism in a substantial proportion of patients.