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Out-of-hospital arrest can occur from multiple etiologies. In patients without an obvious reason for the sudden-death event, diagnostic evaluation is not clear. This study is to determine if early imaging with a head-to-pelvis CT scan may improve diagnostic accuracy, speed of diagnosis and potentially clinical outcomes.
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Best practices for survivors of out-of-hospital sudden death are underdeveloped and untested. Early diagnosis in sudden death survivors is challenging due to patient intubation and obtundation, limited history, and imprecise standard of care testing. Sudden death without an obvious cause (termed "idiopathic sudden death") is primarily caused by cardiovascular disease although a large number of cases result from non-cardiac disease. Improvements in computed tomography (CT) technologies provides a means to identify up to 86% of idiopathic causes of sudden death, including cardiovascular and coronary artery disease, cerebral disease, pulmonary embolism and abdominal catastrophe4 as well as secondary injury from cardiopulmonary resuscitation. To date, use of early CT scans on consecutive sudden death survivors has not been reported. The innovation of this pilot trial is to be first to test whether a comprehensive head-to-pelvis, ECG-gated contrast CT scan (CT-First) can identify the majority of causes for idiopathic sudden death. The significance of CT-First approach is potentially reducing diagnostic errors, treatment delays and inappropriate treatments to potentially improve clinical outcomes in this very high risk population. The expertise of the medical centers involved, combined with the highly respected Medic One service, provide an unusual opportunity to test this diagnostic paradigm with cutting edge CT technologies. The data generated from this study will be used to plan larger randomized trials of early contrast CT scanning versus invasive coronary angiography in sudden death survivors and may be extrapolated to other patient populations such as possible acute coronary syndrome or after trauma.
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Data sourced from clinicaltrials.gov
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