TY - JOUR
T1 - Physicians Estimates of the Probability of Myocardial Infarction in Emergency Boom Patients with chest Pain
AU - Tierney, William M.
AU - Fitzgerald, John
AU - Mchenry, Ross
AU - Roth, Bruce J.
AU - Psaty, Bruce
AU - Stump, David L.
AU - Anderson, F. Kim
PY - 1986/2
Y1 - 1986/2
N2 - 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.
AB - 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.
KW - myocardial infarction
KW - prediction
KW - probability
UR - http://www.scopus.com/inward/record.url?scp=0022643235&partnerID=8YFLogxK
U2 - 10.1177/0272989X8600600103
DO - 10.1177/0272989X8600600103
M3 - Article
C2 - 3945181
AN - SCOPUS:0022643235
SN - 0272-989X
VL - 6
SP - 12
EP - 17
JO - Medical Decision Making
JF - Medical Decision Making
IS - 1
ER -