Annals of Emergency Medicine
Volume 47, Issue 5 , Page 447.e1, May 2006

Prospective Multicenter Study of Quantitative Pretest Probability Assessment to Exclude Acute Coronary Syndrome for Patients Evaluated in Emergency Department Chest Pain Units

  • Alice M. Mitchell, MD, MS

      Affiliations

    • Department of Emergency Medicine, Carolinas Medical Center, Charlotte, NC
  • ,
  • J. Lee Garvey, MD

      Affiliations

    • Department of Emergency Medicine, Carolinas Medical Center, Charlotte, NC
  • ,
  • Abhinav Chandra, MD

      Affiliations

    • Department of Emergency Medicine, Duke University Medical Center, Durham, NC
  • ,
  • Deborah Diercks, MD

      Affiliations

    • Department of Emergency Medicine, University of California–Davis, Sacramento, CA
  • ,
  • Charles V. Pollack, MD, MA

      Affiliations

    • Department of Emergency Medicine, Pennsylvania Hospital, Philadelphia, PA
  • ,
  • Jeffrey A. Kline, MD

      Affiliations

    • Department of Emergency Medicine, Carolinas Medical Center, Charlotte, NC
    • Corresponding Author InformationAddress for correspondence: Jeffrey A. Kline, MD, Department of Emergency Medicine, Carolinas Medical Center, PO Box 32861, Charlotte, NC 28323-2861; 704-355-7092, fax 704-355-7047

Received 17 May 2005; received in revised form 3 August 2005 and 20 September 2005; accepted 5 October 2005. published online 20 January 2006.

Study objective

We compare the diagnostic accuracy of 3 methods—attribute matching, physician’s written unstructured estimate, and a logistic regression formula (Acute Coronary Insufficiency-Time Insensitive Predictive Instrument, ACI-TIPI)—of estimating a very low pretest probability (≤2%) for acute coronary syndromes in emergency department (ED) patients evaluated in chest pain units.

Methods

We prospectively studied 1,114 consecutive patients from 3 academic EDs, evaluated for acute coronary syndrome. Physicians collected data required for pretest probability assessment before protocol-driven chest pain unit testing. A pretest probability greater than 2% was considered “test positive.” The criterion standard was the outcome of acute coronary syndrome (death, myocardial infarction, revascularization, or >60% stenosis prompting new treatment) within 45 days, adjudicated by 3 independent reviewers.

Results

Fifty-one of 1,114 enrolled patients (4.5%; 95% confidence interval [CI] 3.4% to 6.0%) developed acute coronary syndrome within 45 days, including 4 of 991 (0.4%; 95% CI 0.1% to 1.0%) patients, discharged after a negative chest pain unit evaluation result, who developed acute coronary syndrome. Unstructured estimate identified 293 patients with pretest probability less than or equal to 2%, 2 had acute coronary syndrome, yielding sensitivity of 96.1% (95% CI 86.5% to 99.5%) and specificity of 27.4% (95% CI 24.7% to 30.2%). Attribute matching identified 304 patients with pretest probability less than or equal to 2%; 1 had acute coronary syndrome, yielding a sensitivity of 98.0% (95% CI 89.6% to 99.9%) and a specificity of 26.1% (95% CI 23.6% to 28.7%). ACI-TIPI identified 56 patients; none had acute coronary syndrome, yielding sensitivity of 100% (95% CI 93.0% to 100%) and specificity of 6.1% (95% CI 4.7% to 7.9%).

Conclusion

In a low-risk ED population with symptoms suggestive of acute coronary syndrome, patients with a quantitative pretest probability less than or equal to 2%, determined by attribute matching, unstructured estimate, or logistic regression, may not require additional diagnostic testing.

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 Supervising editor: Judd E. Hollander, MDAuthor contributions: This study was designed by JAK, who also obtained research funding. AMM, AC, DD, and JAK supervised and conducted the study, including the recruiting of study participants, collection of data, and conduction of follow-up. JLG, AC, and CVP performed adjudication of study outcomes. Primary data analysis was performed by AMM, who drafted the manuscript. JAK and CVP provided advice on design and statistical analysis. All authors contributed significantly to the revisions of the manuscript. JAK takes responsibility for the paper as a whole.Funding and support: This study was funded by an Emergency Medicine Foundation–Riggs Policy grant 2003-2004. Jeffrey A. Kline is an inventor on a patent (pending) related to attribute matching and owns stock in BreathQuant Medical Systems Inc.Reprints not available from the authors.

PII: S0196-0644(05)01848-2

doi:10.1016/j.annemergmed.2005.10.013

Annals of Emergency Medicine
Volume 47, Issue 5 , Page 447.e1, May 2006