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Emergency physician estimates of the probability of acute coronary syndrome in a cohort of patients enrolled in a study of coronary computed tomographic angiography

Published online by Cambridge University Press:  11 May 2015

Chuen Peng Lee
Affiliation:
Department of Respiratory and Critical Care Medicine, Tan Tock Seng Hospital, Singapore
Udo Hoffmann
Affiliation:
Department of Cardiac Imaging, Massachusetts General Hospital, Boston, MA
Fabian Bamberg
Affiliation:
Department of Cardiac Imaging, Massachusetts General Hospital, Boston, MA
David F. Brown
Affiliation:
Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA
Yuchaio Chang
Affiliation:
Department of General Internal Medicine, Massachusetts General Hospital, Boston, MA
Clifford Swap
Affiliation:
Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA
Blair A. Parry
Affiliation:
Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA
John T. Nagurney*
Affiliation:
Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA
*
Department of Emergency Medicine, Massachusetts General Hospital, Zero Emerson Place, Suite 3b, Boston, MA 02114; [email protected]

Abstract

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Introduction:

Little information exists regarding how accurately emergency physicians (EPs) predict the probability of acute coronary syndrome (ACS). Our objective was to determine if EPs can accurately predict ACS in a prospectively identified cohort of emergency department (ED) patients who met enrolment criteria for a study of coronary computed tomographic angiography (CCTA) and were admitted for a “rule out ACS” protocol.

Methods:

A prospective observational pilot study in an academic medical centre was carried out. EPs caring for patients with chest pain provided whole-number estimates of the probability of ACS after clinical review. This substudy was part of the now published Rule Out Myocardial Infarction/Ischemia Using Computer Assisted Tomography (ROMICAT) study, a study of CCTA and admission of patients for a rule out ACS protocol after a nondiagnostic evaluation. Predictions were grouped into probability groups based on the validated Goldman criteria. ACS was determined by an adjudication committee using American Heart Association/American College of Cardiology/European Society of Cardiology guidelines.

Results:

A total of 334 predictions were obtained for a study population with a mean age of 54 (SD 12) years, 63% of whom were male. There were 35 ACS events. EPs predicted ACS better than by chance, and increasingly higher estimates were associated with a higher incidence of ACS (p = 0.0004). The percentage of patients with ACS was 0%, 6%, 7%, and 17%, respectively, for very low, low, intermediate, and high probability groups. EPs' estimates had a sensitivity of 63% using a > 20% probability of ACS to define a positive test. Lowering this threshold to > 7% to define a test as positive increased the sensitivity of physician estimates to 89% but lowered specificity from 65% to 24%

Conclusions:

Our data suggest that for a selected ED cohort meeting eligibility criteria for a study of CCTA, EPs predict ACS better than by chance, with an increasing proportion of patients proving to have ACS with increasing probability estimates. Lowering the estimate threshold does not result in an overall sensitivity level that is sufficient to send patients home from the ED and is associated with a poor specificity.

Type
Original Research • Recherche originale
Copyright
Copyright © Canadian Association of Emergency Physicians 2012

References

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