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A Janosi

Publications and source records attributed to A Janosi.

12 recordsLinked to original sources
PubMed1992

Usefulness of exercise-induced ST-segment depression in the inferior leads during exercise testing as a marker for coronary artery disease.

Multiple lead systems are shown to have a higher sensitivity than that of single leads for detecting coronary artery disease (CAD) during exercise testing, but the value of ST-segment depression isolated to the inferior leads is questionable. To ascertain the diagnostic accuracy of inferior limb lead II compared with that of precordial lead V5, a retrospective analysis of 173 men was performed (108 in a training population and 65 in a validation cohort). All patients had a standard exercise test and underwent diagnostic coronary angiography within 15 days of the exercise test (range 1 to 65). Sixty-three patients had greater than or equal to 1 coronary stenoses greater than or equal to 70%, or left main lesion greater than or equal to 50%, whereas 45 patients in the training population did not. Exclusion criteria were female sex, left ventricular hypertrophy, left bundle branch block or resting ST-segment depression on the baseline electrocardiogram, previous myocardial infarction or revascularization procedures, and any significant valvular or congenital heart disease. Lead V5 had a better combination of sensitivity (65%) and specificity (84%) (chi-square = 24.11; p less than 0.001) than that of lead II (sensitivity 71%, specificity 44%) (chi-square = 2.25; p = 0.13) at a single cut point, and this improved specificity was substantial (95% confidence interval for observed difference 22 to 58%). Receiver-operating characteristic curve analysis also revealed that lead V5 (area = 0.759) was markedly superior to lead II (area = 0.582) over multiple cut points (z = 3.032; 2p = 0.002).(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗
PubMed1992

Computer probability estimates of angiographic coronary artery disease: transportability and comparison with cardiologists' estimates.

A computer algorithm for estimating probabilities of any significant coronary obstruction and triple vessel/left main obstructions was derived, validated, and compared with the assessments of cardiac clinician angiographers. The algorithm performed at least as well as the clinicians when the latter knew the identity of the patients whose angiograms they had decided to perform. The clinicians were more accurate when they did not know the identity of the subjects but worked from tabulated objective data. Referral and value induced bias may affect physician judgment in assessing disease probability. Application of computer aids or consultation with cardiologists not directly involved with patient management may assist in more rational assessments and decision making.

Adult↗
PubMed1992

Exercise-induced ST depression and ST/heart rate index to predict triple-vessel or left main coronary disease: a multicenter analysis.

The aim of this investigation was to determine the difference in accuracy between two frequently published noninvasive indicators of severity of coronary artery disease (exercise-induced ST segment depression and heart rate-adjusted ST depression [ST/HR index]). The study was designed as a survey of consecutive patients undergoing exercise electrocardiography and coronary angiography. There were a total of 2,270 patients without prior myocardial infarction or cardiac valvular disease referred for angiography from eight institutions in three countries; 401 of these patients had triple-vessel or left main coronary artery disease. The sensitivities of ST depression and ST/HR index in detecting triple-vessel or left main coronary artery disease were, respectively, 75% and 78% (p = 0.08) at cut point values where their specificities were equal (64%). This small increase in the accuracy of the ST/HR index was evident only at peak exercise heart rates below the median value of 132 beats/min, where the sensitivities of ST depression and ST/HR index were 73% and 76% (p = 0.03), respectively, at cut point values corresponding to a specificity of 60%. These results were consistent at all eight participating institutions. The increase in accuracy achieved by dividing exercise-induced ST depression by heart rate is small and confined exclusively to a low exercise heart rate. This lack of superiority cannot be generalized to all methods of heart rate adjustment.

Bias↗
PubMed1991

Algorithm to predict triple-vessel/left main coronary artery disease in patients without myocardial infarction. An international cross validation.

Logistic regression was applied to the clinical, risk factor, and exercise data of consecutive angiographic referrals without prior myocardial infarction to determine an algorithm predicting the probability of triple-vessel/left main coronary artery disease. These data were obtained from a total of 1,074 such subjects from patient populations at four centers (Cleveland Clinic Foundation, Cleveland, Ohio; Hungarian Institute of Cardiology, Budapest, Hungary; the university hospitals, Zurich and Basel, Switzerland; and the Veterans Administration Medical Center, Long Beach, Calif.) and used to derive four separate probability algorithms. Each algorithm is based on patient data from study samples at three of the four centers and consists of 272 logistic functions, which are related to linear combinations of 13 variables (age, sex, type of chest pain, systolic blood pressure, resting electrocardiogram, serum cholesterol, fasting blood sugar, achieved exercise work load, achieved heart rate, exercise-induced angina and hypotension, heart rate-adjusted resting ST depression, and exercise ST slope). The four algorithms were cross validated by testing them on the populations not involved in their derivation. The resulting probabilities in the four test groups were then compared with the angiographic findings of triple-vessel/left main coronary artery disease. The discriminatory power of all the algorithms was fair to good (area under receiver operating characteristic curve, 0.68, 0.75, 0.82, 0.85) in the test groups. The algorithm did not significantly underestimate or overestimate disease probability except in one center (Long Beach).(ABSTRACT TRUNCATED AT 250 WORDS)

Algorithms↗
PubMed1989

International application of a new probability algorithm for the diagnosis of coronary artery disease.

A new discriminant function model for estimating probabilities of angiographic coronary disease was tested for reliability and clinical utility in 3 patient test groups. This model, derived from the clinical and noninvasive test results of 303 patients undergoing angiography at the Cleveland Clinic in Cleveland, Ohio, was applied to a group of 425 patients undergoing angiography at the Hungarian Institute of Cardiology in Budapest, Hungary (disease prevalence 38%); 200 patients undergoing angiography at the Veterans Administration Medical Center in Long Beach, California (disease prevalence 75%); and 143 such patients from the University Hospitals in Zurich and Basel, Switzerland (disease prevalence 84%). The probabilities that resulted from the application of the Cleveland algorithm were compared with those derived by applying a Bayesian algorithm derived from published medical studies called CADENZA to the same 3 patient test groups. Both algorithms overpredicted the probability of disease at the Hungarian and American centers. Overprediction was more pronounced with the use of CADENZA (average overestimation 16 vs 10% and 11 vs 5%, p less than 0.001). In the Swiss group, the discriminant function underestimated (by 7%) and CADENZA slightly overestimated (by 2%) disease probability. Clinical utility, assessed as the percentage of patients correctly classified, was modestly superior for the new discriminant function as compared with CADENZA in the Hungarian group and similar in the American and Swiss groups. It was concluded that coronary disease probabilities derived from discriminant functions are reliable and clinically useful when applied to patients with chest pain syndromes and intermediate disease prevalence.

Algorithms↗
PubMed1988

Factors affecting sensitivity and specificity of a diagnostic test: the exercise thallium scintigram.

Technical and methodological factors might affect the reported accuracies of diagnostic tests. To assess their influence on the accuracy of exercise thallium scintigraphy, the medical literature (1977 to 1986) was non-selectively searched and meta-analysis was applied to the 56 publications thus retrieved. These were analyzed for year of publication, sex and mean age of patients, percentage of patients with angina pectoris, percentage of patients with prior myocardial infarction, percentage of patients taking beta-blocking medications, and for angiographic referral (workup) bias, blinding of tests, and technical factors. The percentage of patients with myocardial infarction had the highest correlation with sensitivity (0.45, p = 0.0007). Only the inclusion of subjects with prior infarction and the percentage of men in the study group were independently and significantly (p less than 0.05) related to test sensitivity. Both the presence of workup bias and publication year adversely affected specificity (p less than 0.05). Of these two factors, publication year had the strongest association by stepwise linear regression. This analysis suggests that the reported sensitivity of thallium scintigraphy is higher and the specificity lower than that expected in clinical practice because of the presence of workup bias and the inappropriate inclusion of post-infarct patients.

Adult↗
PubMed1988

The prognostic value of the exercise test.

Numerous investigators have demonstrated that responses to exercise testing enable prediction of the severity of underlying coronary disease and the patient's prognosis. However, exercise testing cannot predict angiographic findings or a poor prognosis with absolute certainty. Because survival can only be improved in specific clinical subsets of patients, it is important to carefully select for catheterization those in whom intervention can improve both quality and quantity of life. To deliver cost-effective health care, an effort has been made to use decision analysis to select those who should undergo cardiac catheterization. Decision analysis depends on reliable information regarding the predictive accuracy of the exercise test. Thus, this review is timely. Recent studies investigating the prognostic value of the exercise test are reviewed in this monograph. Patients include those recovering from a recent myocardial infarction (MI), those with stable coronary heart disease (including studies that have considered coronary angiographic findings, cardiac end points, and/or improved survival with coronary artery bypass surgery), and apparently healthy individuals. From this review, we conclude that silent ischemia induced by exercise testing in apparently healthy men is not as predictive of a poor outcome as once thought. Also, the use of the exercise test for screening is even more misleading than previously appreciated because of the higher rate of false positive results. Review of the 24 available studies of exercise testing in post-MI patients demonstrates that clinical judgment can be used to identify the high-risk patients, and that ST-segment shifts are not as predictive of high risk as an abnormal systolic blood pressure response or a poor exercise capacity. In patients with stable coronary heart disease, studies considering angiographic findings, cardiac events, and the differential outcome of coronary artery bypass surgery as compared with medical therapy have shown the exercise test to have prognostic power. From this perspective, it is obvious that there is much information supporting the use of exercise testing as the first noninvasive step after the history, physical examination, and resting electrocardiogram in the prognostic evaluation of patients with coronary artery disease. It accomplishes both purposes of prognostic testing: to provide information regarding the patient's status, and to help make recommendations for optimal management. The exercise test results help us make reasonable decisions for selection of patients who should undergo coronary angiography-including quality-of-life issues.(ABSTRACT TRUNCATED AT 400 WORDS)

Aged↗
PubMed1988

Reliability of Bayesian probability analysis for predicting coronary artery disease in a veterans hospital.

To assess the accuracy of Bayesian probability analysis for the prediction of coronary artery disease, post-test probabilities were generated by the application of three Bayesian algorithms to the clinical and noninvasive test results of 199 patients undergoing angiography in a veterans' hospital. All assumed conditional independence but each used different pre-test and conditional probabilities. Two statistical approaches were employed: (1) Sorting of patients in ascending deciles of probability and comparing expected and observed probabilities in each decile. (2) Calculation of normally distributed reliability statistics which do not depend on probability subsets and the comparison of resulting probability distributions using these statistics. Both statistical approaches revealed that the Bayesian algorithms overestimated disease probability when it was high and underestimated it when low. Though all three algorithms were frequently incorrect, they differed significantly in their accuracies, suggesting that errors in Bayesian analysis are caused by factors other than the assumption of independence. The errors may be due to differences in sensitivity and specificity of tests applied in different institutions.

Adult↗
PubMed1988

Methodologic problems in exercise testing research. Are we solving them?

To evaluate the comparative effects of methodologic factors on the reported accuracies of two standard exercise tests, 56 publications comparing the exercise thallium scintigram with the coronary angiogram were analyzed for conformation to five methodologic standards. Analyzed were adequate definition of study group, avoidance of a limited challenge group, avoidance of workup bias, and blinded analysis of the coronary angiogram and myocardial scintigram. Study group characteristics and technical factors were also reviewed. Better conformation with methodologic standards was found than has been reported previously for treadmill exercise testing. Furthermore, study group characteristics and technical factors were better predictors of sensitivity and specificity than were methodologic deficiencies. Only workup bias and test blinding were significantly associated with test accuracy. The percentage of patients with previous myocardial infarction had the highest correlation and was independently and directly related to sensitivity and inversely related to specificity.

Coronary Angiography↗
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↗