Comparison of the multivariate analysis and CADENZA systems for determination of the probability of coronary artery disease

Greenberg, Paul S.; Ellestad, Myrvin H.; Clover, Robert C.

doi:10.1016/0002-9149(84)90019-5

Cited by 28 publications

(3 citation statements)

References 11 publications

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“…Although test sensitivity did drop from 91 to 73%, the overall correct classification rate rose from 58 to 90%. These results compare favorably with several other re ports [12][13][14][15][16][17][19][20][21][22] of improved diagnostic accuracy of ETT in women using multivariate analysis. As methodol ogy can vary considerably, several aspects of this study should be appreciated.…”

Section: Discussionsupporting

confidence: 70%

The Value of Ten Common Exercise Tolerance Test Measures in Predicting Coronary Disease in Symptomatic Females

Richardson

Holly

Amsterdam³

et al. 1995

Cardiology

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The diagnostic contribution often common exercise tolerance test (ETT) measures compared with coronary angiography was studied in 62 symptomatic females (mean age = 53 ± 9 years). Logistic regression revealed that maximal ST-segment depression, the percent of predicted maximal heart rate achieved, and test chest pain all contributed unique predictive information and formed a model generating probabilities for coronary disease (CAD). Using a predicted probability for the presence of CAD of 0.50 as a cutpoint, test accuracy was markedly improved (sensitivity = 73%, specificity = 94%, and overall correct classification rate = 90%) over the standard ST response. We conclude that multivariate analysis using these three easily assessed ETT measures provides superior discrimination between symptomatic women with and without CAD when compared to changes in the ST-segment alone.

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Section: Discussionsupporting

confidence: 70%

The Value of Ten Common Exercise Tolerance Test Measures in Predicting Coronary Disease in Symptomatic Females

Richardson

Holly

Amsterdam³

et al. 1995

Cardiology

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“…Although such an estimate can be derived from readily available population-based data such as the Framingham models and other published summaries [13][14][15]20 that were provided to the CEPP as background information, the utility of making the estimate is less clear. To the extent that such an estimate of future risk reflects only the natural history of a disease such as CAD, without taking into consideration possible actions that might alter that risk, that estimate can only be seen as a reference value rather than a reliable predictor.…”

Section: Discussionmentioning

confidence: 99%

Influence of 99mTc-tetrofosmin SPECT myocardial perfusion imaging on the prediction of future adverse cardiac events

Jain

Lessig

Patel

et al. 2009

Journal of Nuclear Cardiology

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“…Clinical chemical variables have so far not been used as parameters in mathematical models to predict acute myocardial infarction. Some, mainly total cholesterol and glucose, were employed in predictive models for chronic coronary artery disease [18,[22][23][24][25][26][27][28][29][30][31][32]. Others, such as maximum levels of cardiospecific enzymes, were used for stratifying the individual risk of patients for adverse events following myocardial infarction [33] and blood glucose in diabetics in early risk stratification of patients with acute myocardial infarction [34].…”

Section: Discussionmentioning

confidence: 99%

Simple Computer-Assisted Diagnosis of Acute Myocardial Infarction in Patients with Acute Thoracic Pain

Dilger

Pietsch-Breitfeld²,

Stein³

et al. 1992

Methods Inf Med

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Abstract:In order to minimize the initial diagnostic uncertainty in patients suspected of having acute myocardial infarction, we prospectively extracted predictive variables from previous history, ECG, and clinical chemical parameters of 87 patients, who were admitted for acute thoracic pain. The variables thus extracted were: Thoracic pain in previous history, duration of pain, white blood cell count, blood glucose, creatine-kinase, and S-T elevation in the ECG. These parameters were used for formulating a mathematical model based upon univariate and multivariate statistical methods. The sensitivity of the model in the study population was 95% and the specificity 77%. Correct classification was achieved in 89% of cases.In a second phase, the prognostic index was prospectively evaluated in a second set of 122 consecutive patients. In this test population, the sensitivity was 89% and the specificity 86%. 87% of patients were classified correctly.

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Comparison of the multivariate analysis and CADENZA systems for determination of the probability of coronary artery disease

Cited by 28 publications

References 11 publications

The Value of Ten Common Exercise Tolerance Test Measures in Predicting Coronary Disease in Symptomatic Females

The Value of Ten Common Exercise Tolerance Test Measures in Predicting Coronary Disease in Symptomatic Females

Influence of 99mTc-tetrofosmin SPECT myocardial perfusion imaging on the prediction of future adverse cardiac events

Simple Computer-Assisted Diagnosis of Acute Myocardial Infarction in Patients with Acute Thoracic Pain

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