Using the patient's history to estimate the probability of coronary artery disease: a comparison of primary care and referral practices

Abstract

Purpose: According to probability theory, the interpretation of new information should depend on the prior probability of disease. We asked if this principle applies to interpreting the history in patients with chest pain. We compared the prevalence of coronary artery disease (CAD) in patients who had similar histories but who came from populations with different disease prevalence.

Patients and methods: We studied two high-disease-prevalence populations (patients referred for coronary arteriography) and two low-disease-prevalence populations (patients from primary care practices). We used clinical characteristics of one arteriography population to develop a logistic rule for estimating the probability of coronary artery narrowing. The number of clinical findings determined the logistic score, which was proportional to the prevalence of CAD.

Results: The prevalence of CAD was much lower in the primary care population than in the arteriography population, even when patients with similar logistic scores, and thus similar clinical histories, were compared.

Conclusion: A clinician must take account of the overall prevalence of disease in the clinical setting when using the patient's history to estimate the probability of disease. Failure to observe this caution may lead to errors in test selection and interpretation.