RESUMEN
BACKGROUND: Large-vessel occlusion (LVO) stroke represents one-third of acute ischemic stroke (AIS) in the United States but causes two-thirds of poststroke dependence and >90% of poststroke mortality. Prehospital LVO stroke detection permits efficient emergency medical systems (EMS) transport to an endovascular thrombectomy (EVT)-capable center. Our primary objective was to determine the feasibility of using a cranial accelerometry (CA) headset device for prehospital LVO stroke detection. Our secondary objective was development of an algorithm capable of distinguishing LVO stroke from other conditions. METHODS: We prospectively enrolled consecutive adult patients suspected of acute stroke from 11 study hospitals in four different U.S. geographical regions over a 21-month period. Patients received device placement by prehospital EMS personnel. Headset data were matched with clinical data following informed consent. LVO stroke diagnosis was determined by medical chart review. The device was trained using device data and Los Angeles Motor Scale (LAMS) examination components. A binary threshold was selected for comparison of device performance to LAMS scores. RESULTS: A total of 594 subjects were enrolled, including 183 subjects who received the second-generation device. Usable data were captured in 158 patients (86.3%). Study subjects were 53% female and 56% Black/African American, with median age 69 years. Twenty-six (16.4%) patients had LVO and 132 (83.6%) were not LVO (not-LVO AIS, 33; intracerebral hemorrhage, nine; stroke mimics, 90). COVID-19 testing and positivity rates (10.6%) were not different between groups. We found a sensitivity of 38.5% and specificity of 82.7% for LAMS ≥ 4 in detecting LVO stroke versus a sensitivity of 84.6% (p < 0.0015 for superiority) and specificity of 82.6% (p = 0.81 for superiority) for the device algorithm (CA + LAMS). CONCLUSIONS: Obtaining adequate recordings with a CA headset is highly feasible in the prehospital environment. Use of the device algorithm incorporating both CA and LAMS data for LVO detection resulted in significantly higher sensitivity without reduced specificity when compared to the use of LAMS alone.
RESUMEN
Background: Eastern equine encephalitis virus is a mosquito-borne alphavirus responsible for unpredictable outbreaks of severe neurologic disease in animals and humans. While most human infections are asymptomatic or clinically nonspecific, a minority of patients develops encephalitic disease, a devastating illness with a mortality rate of ≥30%. No treatments are known to be effective. Eastern equine encephalitis virus infection is rare in the United States, with an annual average nationwide incidence of 7 cases between 2009 and 2018. However, in 2019, 38 cases were confirmed nationwide, including 10 in Michigan. Methods: Data from 8 cases identified by a regional network of physicians in southwest Michigan were abstracted from clinical records. Clinical imaging and histopathology were aggregated and reviewed. Results: Patients were predominantly older adults (median age, 64 years), and all were male. Results of initial arboviral cerebrospinal fluid serology were frequently negative, and diagnosis was not made until a median of 24.5 days (range, 13-38 days) after presentation, despite prompt lumbar punctures in all patients. Imaging findings were dynamic and heterogeneous, with abnormalities of the thalamus and/or basal ganglia, and prominent pons and midbrain abnormalities were displayed in 1 patient. Six patients died, 1 survived the acute illness with severe neurologic sequelae, and 1 recovered with mild sequelae. A limited postmortem examination revealed diffuse meningoencephalitis, neuronophagia, and focal vascular necrosis. Conclusions: Eastern equine encephalitis is a frequently fatal condition whose diagnosis is often delayed, and for which no effective treatments are known. Improved diagnostics are needed to facilitate patient care and encourage the development of treatments.