4.5 Article

Prospective study of a non-restrictive decision rule for acute aortic syndrome

期刊

AMERICAN JOURNAL OF EMERGENCY MEDICINE
卷 35, 期 9, 页码 1309-1313

出版社

W B SAUNDERS CO-ELSEVIER INC
DOI: 10.1016/j.ajem.2017.04.014

关键词

Computed tomography; Aorta dissection; Aorta rupture; Radiation exposure

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Objectives: To determine the impact of a non-restrictive clinical decision rule on CT utilization for Emergency Department patients suspected of having an acute aortic syndrome (AAS). Methods: We prospectively assessed the performance of a previously described, collaboratively designed, non-restrictive clinical decision rule for AAS. Emergency Department patients with suspected AAS were stratified into low and high-risk groups based on decision rule results, from July 2013-August 2014. Patients with acute trauma, prior AAS or aortic surgery were excluded. CT dose reduction protocols were concurrently implemented as a quality improvement measure. Bivariate analysis was performed to compare the prospective cohort with the historical derivation cohort for CT utilization rates, results of CT, AAS incidence and radiation exposure. The performance of the clinical decision rule was evaluated. Results: Compared with the historic cohort, the study cohort demonstrated a lower CT utilization rate [0.344% (427/124,093) versus 0.477% (1465/306,961), (p < 0.001)], a trend toward higher CT diagnostic yield [4.4% (19/427) versus 2.7% (40/1465), (p = 0.08)]. AAS incidence was similar [0.015% (19/124,093) versus 0.013% (40/306,961), (p = 0.57)]. The mean effective radiation dose was markedly lower [12 +/- 5.5 mSv versus 43 +/- 20mSv,(p < 0.0001)]. The clinical decision rule correctly stratified only 56% (10/18) of patients with AAS as high-risk. Conclusions: A non-restrictive, collaboratively designed, clinical decision rule for Emergency Department patients with suspected AAS performed poorly in risk-stratifying patients for AAS. However, its implementation was associated with a significant and safe decrease in CT utilization. (C) 2017 Elsevier Inc. All rights reserved.

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