Physicians' Estimates of the Probability of Myocardial Infarction in Emergency Boom Patients with chest Pain

William M. Tierney, John Fitzgerald, Ross McHenry, Bruce J. Roth, Bruce Psaty, David L. Stump and F. Kim Anderson

Medical Decision Making, 1986, vol. 6, issue 1, 12-17

Abstract: To evaluate the ability of emergency room physicians to estimate the probability of myocardial infarction in patients with acute chest pain, the authors gathered historical, physical, and electrocardiographic information from 492 patients at the time of their presentation. The physicians admitted 30% of them to intensive care: 53 of the 61 patients with infarctions (sensitivity = 87%) and 96 of the 431 without infarctions (specificity = 78%). Overall, 36% of those admitted had infarctions. The physicians' numeric estimate of the probability of infarction was a good univariate discriminator of infarction, as demonstrated by Receiver Operator Characteristics analysis, and, as indicated by their actual operating point, they seemed to maximize the accuracy of patient classification rather than sensitivity or specificity. Logistic regression analysis identified the physicians' probability estimate as the strongest multivariate predictor of infarction, considering all other clinical information available. Key words: probability; prediction; myocardial infarction. (Med Decis Making 6:12-17, 1986)

Date: 1986
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X8600600103 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:6:y:1986:i:1:p:12-17

DOI: 10.1177/0272989X8600600103

Access Statistics for this article

More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().