A study of the implicit criteria used in diagnosing chest pain

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

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.

Projects and priorities in cardiovascular modeling

Studies that either 1) model the likelihood of clinical outcomes as a function of patient characteristics, or 2) examine the factors underlying a specific medical decision are discussed. Although the currently available models represent important contributions, the working group that met during the 1987 Regenstrief Conference identified several important areas for further attention. Described are discussions on ways to improve standardization, accessibility, validation and dissemination of decision models.

Intermediate, indeterminate, and uninterpretable diagnostic test results

Diagnostic tests do not always yield positive or negative results; sometimes the results are intermediate, indeterminate, or uninterpretable. No consensus exists for the incorporation of such results into data assessment. Conventional Bayesian analysis leads investigators to either exclude patients with non-positive, non-negative results from their studies or categorize such results into inappropriate cells of the standard four-cell decision matrix. The authors propose a standardized method for reporting results in studies dealing with diagnostic test use and discuss how researchers should expand the four-cell matrix to six cells when non-positive, non-negative results occur. They suggest that the six-cell matrix with new operational definitions of sensitivity, specificity, likelihood ratios, and test yield should be adopted routinely. In addition, they define the different types of non-positive, non-negative results and demonstrate how clinicians can use tree-structured decision analysis from the six-cell matrix. While their method does not solve all problems posed by non-positive, non-negative results, it does suggest a standard method for reporting these results and utilizing all the data in decision making.

Exercise testing in suspected coronary artery disease

The interpretation and selection of exercise tests depends on the pretest probability of CAD. Imperfect tests (like exercise tests) provide probability estimates, not definite statements (such as "the patient has CAD" or "the patient does not have CAD"). In patients with a low pretest probability of CAD (asymptomatic persons or men and women with nonanginal chest pain), abnormal exercise test results provide probability estimates that are much too low to conclude that the patient has CAD. In patients with anginal pain and normal exercise tests, the probability of CAD is too high to conclude that the patient has a normal coronary circulation. Exercise tests are not useful for trying to rule out CAD in patients with anginal pain. In patients with an intermediate pretest probability of CAD (men and women with atypical angina and women with typical angina), abnormal exercise tests (particularly the myocardial scintiscan) provide probability estimates that are high enough to justify starting treatment for CAD. Exercise tests are most useful in this group, a conclusion that has been reached by other methods of analysis. The myocardial scintiscan is much more useful than the exercise ECG in women. When CAD is strongly suspected, exercise tests have relatively little diagnostic value but may be useful for prognosis. However, clinical evidence of poor ventricular function may alone suffice to select patients with angina pectoris for coronary arteriography. Conversely, when clinical indicators of congestive heart failure are absent, the prognosis in chronic stable angina is so favorable that any further testing may be unnecessary. Screening asymptomatic persons for CAD is a very low yield practice. Patients who have no cardiac risk factors (hypercholesterolemia, family history of CAD, cigarette smoking, and hypertension) are at especially low risk of a primary cardiac event. Older men with stable typical angina are particularly likely to have left main coronary artery stenosis or three-vessel disease with poor ventricular function. The exercise ECG can identify groups of older men with a relatively high risk of having left main coronary artery stenosis. Physicians should be cautious when applying these recommendations to a primary care practice. The foregoing analysis is based on data obtained from patients who had been selected for coronary arteriography. There are two principal effects of biased selection of study patients: The pretest probability of CAD in clinical subgroups is probably lower than as shown here.(ABSTRACT TRUNCATED AT 400 WORDS)

Systematic bias in recording the history in patients with chest pain

Because of its central importance in medical diagnosis, sources of bias in the patient history must be identified. We report here a study of interobserver agreement in chest pain histories. Histories were obtained by physicians, nurse practitioners, and self-administered questionnaires. We used a discriminant rule to classify the histories as being more or less typical of angina pectoris. A sub-group of the subjects underwent coronary arteriography after the histories were obtained. In subjects with positive coronary arteriograms, physicians consistently obtained histories typical of angina pectoris more often than a self-administered questionnaire. There was no significant systematic bias when comparing physician interviews to the questionnaire among subjects with negative arteriograms nor when comparing two physicians' interviews or a nurse practitioner interview to a questionnaire. When compared to physician interviews, nurse practitioner interviews produced histories less typical of angina pectoris. We conclude that there are systematic differences between the histories obtained by physicians, nurse practitioners, and self-administered questionnaires. Questionnaires can produce biased patient histories and should be carefully validated before being used in patient care activities or health care research.