European journal of emergency medicine : official journal of the European Society for Emergency Medicine
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Diagnosing acute heart failure (AHF) is difficult in elderly patients presenting with acute dyspnea to the emergency department. ⋯ In this study, NT-proBNP alone exhibited the best diagnostic accuracy for diagnosing AHF in elderly patients presenting with acute dyspnea to the emergency departments. None of the other biomarkers alone or combined improved the accuracy compared to NT-proBNP, which is the only biomarker to use in this setting.
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Multicenter Study
Effect of age on the association between the Glasgow Coma Scale and the anatomical brain lesion severity: a retrospective multicentre study.
Background and importance Older adults are at higher risk of undertriage and mortality following a traumatic brain injury (TBI). Early identification and accurate triage of severe cases is therefore critical. However, the Glasgow Coma Scale (GCS) might lack sensitivity in older patients. ⋯ Older adults had increased odds of mortality compared to their younger counterparts at all AIS-head levels: AIS-head = 3 [odds ratio (OR) = 2.9, 95% confidence interval (CI) 1.6-5.5], AIS-head = 4, (OR = 2.7, 95% CI 1.6-4.7) and AIS-head = 5 (OR = 2.6, 95% CI 1.9-3.6) TBI (all P < 0.001). Similar results were found among patients with multiple trauma. Conclusions In this study, among TBI patients with similar AIS-head score, there was a significant higher median GCS in older patients compared to younger patients.
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Background and importance Guidelines recommend that hospital emergency teams locally validate criteria for termination of cardiopulmonary resuscitation in patients with in-hospital cardiac arrest (IHCA). Objective To determine the value of a machine learning algorithm to predict failure to achieve return of spontaneous circulation (ROSC) and unfavourable functional outcome from IHCA using only data readily available at emergency team arrival. Design Retrospective cohort study. ⋯ Five hundred fifty-nine subjects experienced an unfavourable outcome (88.7%). The final classification model to predict unfavourable functional outcomes from IHCA at hospital discharge had an area under the receiver operating characteristic curve of 0.93 (95% CI, 0.92-0.93), a balanced accuracy of 0.59 (95% CI, 0.57-0.61), an F1-score of 0.94 (95% CI, 0.94-0.95), a positive predictive value of 0.91 (0.9-0.91), a negative predictive value of 0.57 (0.48-0.66), a sensitivity of 0.98 (0.97-0.99), and a specificity of 0.2 (0.16-0.24). Conclusion Using data readily available at emergency team arrival, machine learning algorithms had a high predictive power to forecast failure to achieve ROSC and unfavourable functional outcomes from IHCA while cardiopulmonary resuscitation was still ongoing; however, the positive predictive value of both models was not high enough to allow for early termination of resuscitation efforts.
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Emergency departments (EDs) are seeing an increase in patients requiring end-of-life (EOL) care. There is paucity of data of attitudes and knowledge of physicians providing EOL care in the ED both internationally and in Ireland. ⋯ This study has highlighted a lack of awareness and knowledge of EOL care particularly amongst less experienced emergency medicine doctors. Formalized training and education programs in the provision of EOL care in the ED will improve comfort levels and knowledge amongst the emergency medicine doctors and improve the quality of care provided.