One hundred fifty-four patients referred for coronary arteriography were prospectively studied with stress electrocardiography, stress thallium scintigraphy, cine fluoroscopy (for coronary calcifications), and coronary angiography. Pretest probabilities of coronary disease were determined based on age, sex, and type of chest pain. These and pooled literature values for the conditional probabilities of test results based on disease state were used in Bayes' theorem to calculate posttest probabilities of disease. The results of the three noninvasive tests were compared for statistical independence, a necessary condition for their simultaneous use in Bayes' theorem. The test results were found to demonstrate pairwise independence in patients with and those without disease. Some dependencies that were observed between the test results and the clinical variables of age and sex were not sufficient to invalidate application of the theorem. Sixty-eight of the study patients had at least one major coronary artery obstruction of greater than 50%. When these patients were divided into low-, intermediate-, and high-probability subgroups according to their pretest probabilities, noninvasive test results analyzed by Bayesian probability analysis appropriately advanced 17 of them by at least one probability subgroup while only seven were moved backward. Of the 76 patients without disease, 34 were appropriately moved into a lower probability subgroup while 10 were incorrectly moved up. We conclude that posttest probabilities calculated from Bayes' theorem more accurately classified patients with and without disease than did pretest probabilities, thus demonstrating the utility of the theorem in this application.

Angiography↗

PubMed1984

Ventricular arrhythmias and serum potassium: is there a correlation in the arrhythmic patient?

Explore the source record for details and available documents.

Arrhythmias, Cardiac↗

PubMedDate not supplied

Exercise testing: uses and limitations considering recent studies.

Accurate use and interpretation of exercise test results depend on an understanding of physiologic principles, meticulous attention to proper methodology, and realization of the appropriate applications and limitations of testing. Understanding the relationship between myocardial and ventilatory oxygen consumption and exercise test variables will aid in the diagnosis and prognostic evaluation. Use of proper methodology in preparing the patient, performing the examination, and interpreting the results is critical to obtaining the maximum information with maximum safety for each individual patient. Improvements in methodology including the use of the Borg scale to estimate individual effort, abandonment of the predicted maximum heart rate, and the increased use of ventilatory oxygen uptake measurements should be applied. Exercise capacity should not be reported in total time but rather as the VO2 or MET equivalent of the workload achieved. This permits the comparison of the results of many different exercise testing protocols. The most useful exercise ECG variable for the diagnosis of coronary artery disease remains the ST segment shift. Unfortunately, it is not as helpful in localizing myocardial ischemia. Diagnostic accuracy can be improved by adjusting ST depressions for exercise-induced heart rate increase. Accuracy can be further increased by combining ECG, clinical, and radionuclide variables in probabilistic formulas that retain the independent diagnostic information from each variable and accurately predict disease probability. To avoid errors in clinical decision making, care must be used to insure that the mathematical formula used was derived from a population of patients that is similar to those being tested. The clinical applications for exercise testing include diagnosis of patients with chest pain syndromes, determination of disease severity, and prognosis in patients with known coronary artery disease, evaluation of arrhythmias, screening of asymptomatic patients, and evaluation of medical, surgical, and angioplastic therapy for coronary disease. In spite of studies involving thousands of patients, controversy exists regarding the diagnostic power of exercise testing. The large differences in reported accuracies are largely due to methodologic problems that have been encountered by various investigators. Clinicians should be made aware of these problems when reading the literature on ECG and radionuclide exercise testing. Such awareness will help them understand the limitations of these noninvasive procedures.(ABSTRACT TRUNCATED AT 400 WORDS)

Electrocardiography↗

PubMedDate not supplied

The diagnostic accuracy of the exercise electrocardiogram: a meta-analysis of 22 years of research.

Explore the source record for details and available documents.

Adult↗

PubMedDate not supplied

Quantification of coronary arterial calcium by dual energy digital subtraction fluoroscopy.

Clinical studies of the heart with fluoroscopy have shown that fluoroscopic visualization of calcium in the coronary arteries is strongly associated with coronary artery disease. However, fluoroscopic detection is limited by its low sensitivity, which is partly due to the interfering background tissue structures and image quantum noise. Moreover, quantification of the absolute amount of calcium in an arterial segment has not been possible. A real-time dual-energy subtraction technique has been investigated as a possible solution to the above problem. In this energy subtraction technique, the kVp and filtration are switched at 30 Hz. In order to assess the potential utility of this videodensitometric technique to quantitate coronary artery calcium, arterial phantoms and excised segments of diseased human arteries were imaged. The low- and high-energy images were corrected for scatter and veiling glare before subtraction. Calcium measurements were made using the tissue-suppressed energy-subtracted images. The estimated calcium phosphate and ashed weights of the calcified arterial segments (N = 20) were highly correlated (slope = 1.04, Intercept = -0.33 mg, r = 0.92).

Calcium↗

PubMedDate not supplied

The reliability of probability analysis in the prediction of coronary artery disease in two hospitals.

To assess the accuracy of the Bayesian computer program CADENZA for the prediction of coronary artery disease, the authors examined the probabilities generated by the application of this program to the clinical and noninvasive test results of 303 patients in a private referral center and 199 patients in a veterans' hospital. These probabilities were compared with those produced by applying a six-variable discriminant function derived by logistic regression at the private referral center. Two statistical approaches were employed in evaluating the relative performances of the Bayesian program and the discriminant function. The first of these involved the sorting of patients in both test groups into ascending deciles of probability and comparing expected probability with observed angiographic disease prevalence in each decile. The second involved the calculation and comparison of a standardized reliability measure. The latter was significantly lower for the discriminant function both at the private hospital (0.200 for the discriminant function versus -17.5 +/- 1.96 for the Bayesian program) and at the veterans' hospital (-0.8 +/- 1.96 for the discriminant function versus -11.3 for Bayesian program). This suggests that the discriminant function is significantly superior to the Bayesian algorithm CADENZA for predicting coronary artery disease probabilities in subjects who have relatively high pretest disease probabilities.

Bayes Theorem↗

PubMedDate not supplied

Clinical assessment of the probability of coronary artery disease: judgmental bias from personal knowledge.

Probability estimates of angiographic coronary artery disease made by experienced, board-certified staff cardiologists were compared with those of cardiologists in training (fellows). In addition, estimates made before coronary angiography were compared with those made several months later based on written clinical summaries of 15 items of objective clinical and test data. Cardiologists were asked to estimate the probabilities of coronary artery disease, multivessel disease, and triple-vessel or left main disease. The study population consisted of 510 consecutive patients without valvular disease referred for the first time for coronary angiography to three hospitals. Both staff and fellows consistently overestimated the pre-angiographic probability of coronary artery disease. The probabilities estimated from patient summaries were always significantly lower than the pre-angiographic assessments. Only staff cardiologists reliably assessed the probabilities of coronary artery disease during the second assessment (p less than 0.05). Thus, estimates of disease probability based on clinical judgment vary according to the source of information, and these estimates are more accurate when physicians have objective data on hand and do not know the identities of the patients.

Coronary Angiography↗

PubMedDate not supplied

The effect of disease-prevalence adjustments on the accuracy of a logistic prediction model.

The accuracy of a logistic prediction model is degraded when it is transported to populations with outcome prevalences different from that of the population used to derive the model. The resultant errors can have major clinical implications. Accordingly, the authors developed a logistic prediction model with respect to the noninvasive diagnosis of coronary disease based on 1,824 patients who underwent exercise testing and coronary angiography, varied the prevalence of disease in various "test" populations by random sampling of the original "derivation" population, and determined the accuracy of the logistic prediction model before and after the application of a mathematical algorithm designed to adjust only for these differences in prevalence. The accuracy of each prediction model was quantified in terms of receiver operating characteristic (ROC) curve area (discrimination) and chi-square goodness-of-fit (calibration). As the prevalence of the test population diverged from the prevalence of the derivation population, discrimination improved (ROC-curve areas increased from 0.82 +/- 0.02 to 0.87 +/- 0.03; p < 0.05), and calibration deteriorated (chi-square goodness-of-fit statistics increased from 9 to 154; p < 0.05). Following adjustment of the logistic intercept for differences in prevalence, discrimination was unchanged and calibration improved (maximum chi-square goodness-of-fit fell from 154 to 16). When the adjusted algorithm was applied to three geographically remote populations with prevalences that differed from that of the derivation population, calibration improved 87%, while discrimination fell by 1%. Thus, prevalence differences produce statistically significant and potentially clinically important errors in the accuracy of logistic prediction models. These errors can potentially be mitigated by use of a relatively simple mathematical correction algorithm.

Adult↗