Clinical prediction rules for the diagnosis of pulmonary embolism

Abstract

Diagnosing pulmonary embolism is as challenging and controversial today as it was 25 years ago when lung scanning became widely implemented. In 1976, McNeil suggested that ventilation-perfusion lung scans in patients with suspected pulmonary embolism should be classified as normal, or low, high, or “indeterminate” or intermediate probability (1). Diagnosis is confirmed by a high-probability scan and is unlikely in patients with low-probability or normal scans. Patients with indeterminate scans need a pulmonary angiogram to establish disease. Although some authors argued that there were inadequate data to justify the widespread use of lung scans (2), this diagnostic algorithm was widely accepted and is at times used erroneously today. Two prospective series have defined the test characteristics of lung scans (3,4), showing that patients with high-probability scans had about an 87% probability of pulmonary embolism, compared with one third of patients with intermediate-probability scans, and 14% to 31% of those with low-probability scans. Missing 14% to 30% of patients with this potentially lethal disease is unacceptable even if we accept the most favorable result. For this reason, lowand intermediate-probability scans are now designated as nondiagnostic. Because pulmonary embolism is likely to originate in the deep veins of the lower extremities, subsequent albeit imperfect diagnostic strategies included testing for lower extremity venous thrombosis (5). There was much hope that computed tomography would provide more reliable information. Studies show that it is useful in diagnosing other conditions that may be confused with pulmonary embolism, and that it performs adequately to exclude or confirm pulmonary embolism in patients with large central emboli but misses pulmonary embolism in smaller pulmonary arteries (6). Magnetic resonance angiography has also been found to miss pulmonary embolism in smaller pulmonary arteries, but it can be used in patients with contraindications to contrast material (7). Echocardiography has been suggested as a diagnostic tool but awaits further study (8). The most promising new test is the D-dimer test, which has excellent sensitivity, especially if using enzyme-linked immunoassays. Most D-dimer assays are effective in excluding thromboembolism in outpatients, particularly when combined with a clinical picture consistent with low probability of disease (9 –11). The test should not be used in hospitalized patients, because the prevalence of pulmonary embolism is higher in this group, and in other conditions where test results are likely to be abnormal, because of poor specificity. A fundamental principle of diagnostic testing is to consider the likelihood of disease before testing (pretest probability) and to combine it with test results to obtain a post-test probability of disease. Investigators in the Prospective Investigation Of Pulmonary Embolism Diagnosis study demonstrated that experienced clinicians were able to classify patients with suspected pulmonary embolism with some precision based on clinical assessment (3): 9% in the low clinical pretest probability group, 30% in the intermediate group, and 68% in the high-probability group. When the clinical assessment was combined with ventilation-perfusion lung scanning, the probability of pulmonary embolism was refined further. If the clinical assessment and lung scan were concordant, pulmonary embolism was either highly likely (96%) or very unlikely (2%). However, when there was discordance between clinical assessment and lung scan results, the probability was 45% to 56%, and further testing was required. It is unclear if less experienced or nonspecialist physicians would be as successful in predicting pulmonary embolism because the probability estimate is based on clinical impression rather than specific criteria. Hence, explicit prediction rules were developed. In this issue of the Journal, Chagnon et al. (12) compare two such rules—the Wells’ rule and the Geneva rule (13,14). The Wells’ prediction rule was derived from a cohort of consecutive outpatients and inpatients with suspected pulmonary embolism (13). Seven variables associated with pulmonary embolism from a logistic regression model were assigned point values. Patients were classified as having low, intermediate, or high clinical probability (pretest probability) of pulmonary embolism based on point totals. These assessments were predictive of pulmonary embolism in their algorithm; however, their diagAm J Med. 2002;113:337–338. From the Division of General Internal Medicine, Department of Medicine, University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School, New Brunswick, New Jersey. Requests for reprints should be addressed to Jeffrey L. Carson, MD, University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School, 125 Paterson Street, New Brunswick, New Jersey 08903, or carson@umdnj.edu.