Emergency medicine journal : EMJ
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Major incidents (MIs) are an important cause of death and disability. Triage tools are crucial to identifying priority 1 (P1) patients-those needing time-critical, life-saving interventions. Existing expert opinion-derived tools have limited evidence supporting their use. This study employs machine learning (ML) to develop and validate models for novel primary and secondary triage tools. ⋯ Novel triage tools developed using ML outperform existing tools in a nationally representative trauma population. The proposed primary tool requires external validation prior to consideration for practical use. The secondary tool demonstrates good external validity and may be used to support decision-making by healthcare workers responding to MIs.
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The diagnosis of acute aortic syndrome (AAS) is commonly delayed or missed in the ED. We describe characteristics of ED attendances with symptoms potentially associated with AAS, diagnostic performance of clinical decision tools (CDTs) and physicians and yield of CT aorta angiogram (CTA). ⋯ Only 0.3% of patients presenting with potential AAS symptoms had AAS but 7% underwent CTA. CDTs incorporating clinician gestalt appear to be most promising, but further prospective work is needed, including evaluation of the role of D-dimer.