The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
International application of a new probability algorithm for the diagnosis of coronary artery disease
Open accessAbstract
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.
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Cites
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Cited by
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Federated Learning for Healthcare Informatics
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Federated Learning for Healthcare Informatics
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An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction
Samuel, O. W., Asogbon, G. M., Sangaiah, A. K., Fang, P., & Li, G. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.10.020 · Cited by 425
Metadata
- Authors
- Detrano, R., Janosi, A., Steinbrunn, W., Pfisterer, M., Schmid, J.-J., Sandhu, S., Guppy, K. H., Lee, S., & Froelicher, V.
- Venue
- The American Journal of Cardiology
- Publisher
- Elsevier BV
- Published
- 1989-08
- Volume
- 64
- Issue
- 5
- Pages
- 304-310
- ISSN
- 0002-9149 (ISSN-L)
- OpenAlex
- W1989164753
- Cited by
- 695
- References
- 17
- FWCI
- 5.91
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Detrano, R., Janosi, A., Steinbrunn, W., Pfisterer, M., Schmid, J.-J., Sandhu, S., Guppy, K. H., Lee, S., & Froelicher, V. (1989). International application of a new probability algorithm for the diagnosis of coronary artery disease. The American Journal of Cardiology. https://doi.org/10.1016/0002-9149(89)90524-9
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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