Clinician gestalt estimate of pretest probability for acute coronary syndrome and pulmonary embolism in patients with chest pain and dyspnea

摘要

Study objective: Pretest probability helps guide diagnostic testing for patients with suspected acute coronary syndrome and pulmonary embolism. Pretest probability derived from the clinician's unstructured gestalt estimate is easier and more readily available than methods that require computation. We compare the diagnostic accuracy of physician gestalt estimate for the pretest probability of acute coronary syndrome and pulmonary embolism with a validated, computerized method. Methods: This was a secondary analysis of a prospectively collected, multicenter study. Patients (N=840) had chest pain, dyspnea, nondiagnostic ECGs, and no obvious diagnosis. Clinician gestalt pretest probability for both acute coronary syndrome and pulmonary embolism was assessed by visual analog scale and from the method of attribute matching using a Web-based computer program. Patients were followed for outcomes at 90 days. Results: Clinicians had significantly higher estimates than attribute matching for both acute coronary syndrome (17% versus 4%; P.001, paired t test) and pulmonary embolism (12% versus 6%; P.001). The 2 methods had poor correlation for both acute coronary syndrome (r2=0.15) and pulmonary embolism (r2=0.06). Areas under the receiver operating characteristic curve were lower for clinician estimate compared with the computerized method for acute coronary syndrome: 0.64 (95% confidence interval [CI] 0.51 to 0.77) for clinician gestalt versus 0.78 (95% CI 0.71 to 0.85) for attribute matching. For pulmonary embolism, these values were 0.81 (95% CI 0.79 to 0.92) for clinician gestalt and 0.84 (95% CI 0.76 to 0.93) for attribute matching. Conclusion: Compared with a validated machine-based method, clinicians consistently overestimated pretest probability but on receiver operating curve analysis were as accurate for pulmonary embolism but not acute coronary syndrome.