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Background and Purpose: Early detection of large vessel occlusion (LVO) stroke optimizes endovascular therapy and improves outcomes. Clinical stroke severity scales used for LVO identification have variable accuracy. We investigated a portable LVO-detection device (PLD), using electroencephalography and somatosensory-evoked potentials, to identify LVO stroke. Methods: We obtained PLD data in suspected patients with stroke enrolled prospectively via a convenience sample in 8 emergency departments within 24 hours of symptom onset. LVO discriminative signals were integrated into a binary classifier. The National Institutes of Health Stroke Scale was documented, and 4 prehospital stroke scales were retrospectively calculated. We compared PLD and scale performance to diagnostic neuroimaging. Results: Of 109 patients, there were 25 LVO (23%), 38 non-LVO ischemic (35%), 14 hemorrhages (13%), and 32 stroke mimics (29%). The PLD had higher sensitivity (80% [95% CI, 74–85]) and similar specificity (80% [95% CI, 77–83]) to all prehospital scales at their predetermined high probability LVO thresholds. The PLD had high discrimination for LVO ( C -statistic=0.88). Conclusions: The PLD identifies LVO with superior accuracy compared with prehospital stroke scales in emergency department suspected stroke. Future studies need to validate the PLD’s potential as an LVO triage aid in prehospital undifferentiated stroke populations.

Initial results show that we were able to successfully develop, implement, and evaluate performance of first-year medical students on their fundamental knowledge and performance of basic US using a model that emphasized hands-on simulation-enhanced training. Furthermore, most students found the experience to be a beneficial component of their education and indicated a desire for more US training in the medical curricula.

IntroductionTransesophageal echocardiography (TEE) is a well-established method of evaluating cardiac pathology. It has many advantages over transthoracic echocardiography (TTE), including the ability to image the heart during active cardiopulmonary resuscitation. This prospective simulation study aims to evaluate the ability of emergency medicine (EM) residents to learn TEE image acquisition techniques and demonstrate those techniques to identify common pathologic causes of cardiac arrest.MethodsThis was a prospective educational cohort study with 40 EM residents from two participating academic medical centers who underwent an educational model and testing protocol. All participants were tested across six cases, including two normals, pericardial tamponade, acute myocardial infarction (MI), ventricular fibrillation (VF), and asystole presented in random order. Primary endpoints were correct identification of the cardiac pathology, if any, and time to sonographic diagnosis. Calculated endpoints included sensitivity, specificity, and positive and negative predictive values for emergency physician (EP)-performed TEE. We calculated a kappa statistic to determine the degree of inter-rater reliability.ResultsForty EM residents completed both the educational module and testing protocol. This resulted in a total of 80 normal TEE studies and 160 pathologic TEE studies. Our calculations for the ability to diagnose life-threatening cardiac pathology by EPs in a high-fidelity TEE simulation resulted in a sensitivity of 98%, specificity of 99%, positive likelihood ratio of 78.0, and negative likelihood ratio of 0.025. The average time to diagnose each objective structured clinical examination case was as follows: normal A in 35 seconds, normal B in 31 seconds, asystole in 13 seconds, tamponade in 14 seconds, acute MI in 22 seconds, and VF in 12 seconds. Inter-rater reliability between participants was extremely high, resulting in a kappa coefficient across all cases of 0.95.ConclusionEM residents can rapidly perform TEE studies in a simulated cardiac arrest environment with a high degree of precision and accuracy. Performance of TEE studies on human patients in cardiac arrest is the next logical step to determine if our simulation data hold true in clinical practice.

Patients with moderate to severe asthma who receive intravenous methylprednisolone in the prehospital setting have significantly fewer hospital admissions.