ArticleEmergency radiology2023
Can you accurately rule out acute aortic syndrome by restricting imaging of the aorta to the area of the patient's pain?
Article in Emergency radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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5 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundAcute aortic syndrome (AAS) is a life-threatening condition necessitating timely and accurate diagnosis for appropriate treatment. Currently, the only way to rule out the diagnosis is advanced imaging. The most accessible is computed tomography of the entire aorta. Most scans are negative, exposing patients to radiation, increased time in the emergency department (ED), and non-significant incidental findings. This study investigated whether restricting imaging to the area of aortic-related pain accurately rules out AAS.
methodsA health records review was conducted on consecutive cases from three academic EDs between 2015 and 2020. Data were extracted and verified from multiple sources. Participants included adults diagnosed with AAS based on radiological evidence. The diagnostic performance of the restricted imaging strategy was assessed; sensitivity and likelihood ratios with 95% confidence intervals were calculated.
resultsData from 149 cases of AAS were collected, with the majority presenting with chest pain (46%) or abdominal pain (24%). The restricted imaging strategy demonstrated a sensitivity of 96% (95% CI 91.4-98.5%) in ruling out AAS. In a subset of patients with systolic blood pressure > 90 mmHg and without aortic aneurysm/repair (n = 86), the sensitivity was 100% (95% CI 96-100%).
conclusionRestricting imaging to the area of pain in hemodynamically stable patients without known aortic aneurysm provides a highly sensitive approach to ruling out AAS.
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