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Selective Chest Imaging for Blunt Trauma Patients: The National Emergency X-radiography Utilization Studies (NEXUS-Chest Algorithm)
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Oct 29 2016
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Source: Am J Emerg Med. 35(1):164-170.
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Alternative Title:Am J Emerg Med
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Description:Chest imaging plays a prominent role in blunt trauma patient evaluation, but indiscriminate imaging is expensive, may delay care, and unnecessarily exposes patients to potentially harmful ionizing radiation. To improve diagnostic chest imaging utilization, we conducted 3 prospective multicenter studies over 12years to derive and validate decision instruments (DIs) to guide the use of chest x-ray (CXR) and chest computed tomography (CT). The first DI, NEXUS Chest x-ray, consists of seven criteria (Age >60years; rapid deceleration mechanism; chest pain; intoxication; altered mental status; distracting painful injury; and chest wall tenderness) and exhibits a sensitivity of 99.0% (95% confidence interval [CI] 98.2-99.4%) and a specificity of 13.3% (95% CI, 12.6%-14.0%) for detecting clinically significant injuries. We developed two NEXUS Chest CT DIs, which are both highly reliable in detecting clinically major injuries (sensitivity of 99.2%; 95% CI 95.4-100%). Designed primarily to focus on detecting major injuries, the NEXUS Chest CT-Major DI consists of six criteria (abnormal CXR; distracting injury; chest wall tenderness; sternal tenderness; thoracic spine tenderness; and scapular tenderness) and exhibits higher specificity (37.9%; 95% CI 35.8-40.1%). Designed to reliability detect both major and minor injuries (sensitivity 95.4%; 95% CI 93.6-96.9%) with resulting lower specificity (25.5%; 95% CI 23.5-27.5%), the NEXUS CT-All rule consists of seven elements (the six NEXUS CT-Major criteria plus rapid deceleration mechanism). The purpose of this review is to synthesize the three DIs into a novel, cohesive summary algorithm with practical implementation recommendations to guide selective chest imaging in adult blunt trauma patients.
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Pubmed ID:27838036
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Pubmed Central ID:PMC5177494
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Volume:35
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Issue:1
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