Emergency medicine journal : EMJ
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Artificial intelligence (AI)-assisted image interpretation is a fast-developing area of clinical innovation. Most research to date has focused on the performance of AI-assisted algorithms in comparison with that of radiologists rather than evaluating the algorithms' impact on the clinicians who often undertake initial image interpretation in routine clinical practice. This study assessed the impact of AI-assisted image interpretation on the diagnostic performance of frontline acute care clinicians for the detection of pneumothoraces (PTX). ⋯ The study indicates that AI-assisted image interpretation significantly enhances the diagnostic accuracy of clinicians in detecting PTX, particularly benefiting less experienced practitioners. While overall interpretation time remained unchanged, the use of AI improved diagnostic confidence and sensitivity, especially among junior clinicians. These findings underscore the potential of AI to support less skilled clinicians in acute care settings.
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Multicenter Study
Haematoma block is the most efficient technique for closed forearm fracture reduction: a retrospective cohort study.
Forearm fractures are a common ED presentation. This study aimed to compare the resource utilisation of three anaesthetic techniques used for closed forearm fracture reduction in the ED: haematoma block (HB), Bier's block (BB) and procedural sedation (PS). ⋯ In this study, the HB method was the most efficient as it was associated with a shorter ED LOS, lower cost and staff resource utilisation. Although PS had a significantly greater proportion of successful reductions on the first attempt, HB had fewer complications than BB and PS. EDs with limited resources should consider using HB or BB as the initial technique for fracture reduction with PS used for failed HB or when regional blocks are contraindicated.
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Multicenter Study Comparative Study
External validation of the preHEART score and comparison with current clinical risk scores for prehospital risk assessment in patients with suspected NSTE-ACS.
Emergency Medical Services (EMS) studies have shown that prehospital risk stratification and triage decisions in patients with suspected non-ST-elevation acute coronary syndrome (NSTE-ACS) can be improved using clinical risk scores with point-of-care (POC) troponin. In current EMS studies, three different clinical risk scores are used in patients suspected of NSTE-ACS: the prehospital History, ECG, Age, Risk and Troponin (preHEART) score, History, ECG, Age, Risk and Troponin (HEART) score and Troponin-only Manchester Acute Coronary Syndromes (T-MACS). The preHEART score lacks external validation and there exists no prospective comparative analysis of the different risk scores within the prehospital setting. The aim of this analysis is to externally validate the preHEART score and compare the diagnostic performance of the these three clinical risk scores and POC-troponin. ⋯ On external validation, the preHEART demonstrates good overall diagnostic performance as a prehospital risk stratification tool. Both the preHEART and HEART scores have better overall diagnostic performance compared with T-MACS and sole POC-troponin measurement. These data support the implementation of clinical risk scores in prehospital clinical pathways.