Journal
AMERICAN JOURNAL OF EMERGENCY MEDICINE
Volume 31, Issue 11, Pages 1546-1550Publisher
W B SAUNDERS CO-ELSEVIER INC
DOI: 10.1016/j.ajem.2013.06.005
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Funding
- CTSA [UL1 RR025750, KL2 RR025749, TL1 RR025748]
- National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH),
- NIH roadmap for Medical Research
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Objective: Patients with suspected acute aortic syndromes (AAS) often undergo computed tomography (CT) with negative results. We sought clinical and diagnostic criteria to identify low-risk patients, an initial step in developing a clinical decision rule. Methods: We retrospectively identified all adults presenting to our emergency department (ED) from January 1, 2006, to August 1, 2010, who underwent CT angiography for suspected AAS without prior trauma or AAS. A total of 1465 patients met inclusion criteria; a retrospective case-controlled review (ratio 1: 4) was conducted. Cases were diagnosed with aortic dissection, intramural hematoma, penetrating atherosclerotic ulcer, or ruptured aneurysm. Results: Of the patients who underwent CT, 2.7% (40/1465) had an AAS; 2 additional cases were diagnosed after admission (ED miss rate, 5% [2/42]). Patients with AAS were significantly older than controls (66 vs 59 years; P -.008). Risk factors included abnormal chest radiograph (sensitivity, 79% [26/33]; specificity, 82% [113/137]) and acute chest pain (sensitivity, 83% [29/35]; specificity, 71% [111/157]). None of the 19 patients with resolved pain upon ED presentation had AAS. These data support a 2-step rule: first screen for ongoing pain; if present, screen for acute chest pain or an abnormal chest radiograph. This approach achieves a 54% (84/155) reduction in CT usage with a sensitivity for AAS of 96% (95% confidence interval, 89%-100%), negative predictive value of 99.8% (99.4%-100%), and a false-negative rate of 1.7% (1/84). Conclusions: Our results demonstrate a need to safely identify patients at low risk for AAS who can forgo CT. We developed a preliminary 2-step clinical decision rule, which requires validation. (C) 2013 Elsevier Inc. All rights reserved.
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