Media coverage of COVID-19 vaccination-associated cerebral venous sinus thrombosis was followed by a surge in emergency presentations due to headache - observations from a university hospital in Germany.

Nocebo effects describe all negative outcomes for well-being brought about by negative health-related expectations. Media coverage of drug side effects can fuel nocebo effects and lead to increased symptom reports. This retrospective observational analysis of emergency reports at the neurological emergency room at University Hospital Essen, Germany, examines whether media communication about a cumulation of very rare cases of cerebral venous sinus thrombosis (CVST) after COVID-19 vaccination with the AstraZeneca compound (ChAdOx-1 nCoV-19) was followed by an increase in weekly presentation rates of patients with the main complaint of headache, a symptom commonly occurring as a vaccination reaction but also communicated as a warning symptom for CVST. The rate of headache presentations increased by 171.7% during the five weeks after the first announcement of CVSTs in Germany on 11 March 2021, compared to the five weeks immediately prior. Furthermore, more young women sought consultation for headache, reflecting the communicated at-risk profile for CVST. The increased rate of headache presenters contributed to a 32.1% rise in total neurological emergency cases, causing an increased strain on the emergency facility after the side effect risk was publicized. We discuss a causal role of negative side effect expectations after vaccination with AstraZeneca as a driver for this increase. While transparent communication about benefits and potential side effects is crucial for vaccination acceptance, increased vigilance toward nocebo effects in health-related media communication is needed due to its potential harm to the individual and society, especially when emergency medical resources are stretched thin.

Frequency and Characteristics of Non-Neurological and Neurological Stroke Mimics in the Emergency Department.

BACKGROUND: Stroke mimics are common in the emergency department (ED) and early detection is important to initiate appropriate treatment and withhold unnecessary procedures. We aimed to compare the frequency, clinical characteristics and predictors of non-neurological and neurological stroke mimics transferred to our ED for suspected stroke. METHODS: This was a cross-sectional study of consecutive patients with suspected stroke transported to the ED of the University Hospital Essen between January 2017 and December 2021 by the city's Emergency Medical Service. We investigated patient characteristics, preclinical data, symptoms and final diagnoses in patients with non-neurological and neurological stroke mimics. Multinominal logistic regression analysis was performed to assess predictors of both etiologic groups. RESULTS: Of 2167 patients with suspected stroke, 762 (35.2%) were diagnosed with a stroke mimic. Etiology was non-neurological in 369 (48.4%) and neurological in 393 (51.6%) cases. The most common diagnoses were seizures (23.2%) and infections (14.7%). Patients with non-neurological mimics were older (78.0 vs. 72.0 y, p < 0.001) and more likely to have chronic kidney disease (17.3% vs. 9.2%, p < 0.001) or heart failure (12.5% vs. 7.1%, p = 0.014). Prevalence of malignancy (8.7% vs. 13.7%, p = 0.031) and focal symptoms (38.8 vs. 57.3%, p < 0.001) was lower in this group. More than two-fifths required hospitalization (39.3 vs. 47.1%, p = 0.034). Adjusted multinominal logistic regression revealed chronic kidney and liver disease as independent positive predictors of stroke mimics regardless of etiology, while atrial fibrillation and hypertension were negative predictors in both groups. Prehospital vital signs were independently associated with non-neurological stroke mimics only, while age was exclusively associated with neurological mimics. CONCLUSIONS: Up to half of stroke mimics in the neurological ED are of non-neurological origin. Preclinical identification is challenging and a high proportion requires hospitalization. Awareness of underlying etiologies and differences in clinical characteristics is important to provide optimal care.

Validation of a shortened FAST-ED algorithm for smartphone app guided stroke triage.

BACKGROUND AND PURPOSE: Large vessel occlusion (LVO) recognition scales were developed to identify patients with LVO-related acute ischemic stroke (AIS) on the scene of emergency. Thus, they may enable direct transport to a comprehensive stroke centre (CSC). In this study, we aim to validate a smartphone app-based stroke triage with a shortened form of the Field Assessment Stroke Triage for Emergency Destination (FAST-ED). METHODS: This retrospective validation study included 2815 patients with confirmed acute stroke and suspected acute stroke but final diagnosis other than stroke (stroke mimics) who were admitted by emergency medical service (EMS) to the CSC of the Neurological University Hospital Essen, Germany. We analysed the predictive accuracy of a shortened digital app-based FAST-ED ( 'FAST-ED App') for LVO-related AIS and yield comparison to various other LVO recognition scales. RESULTS: The shortened FAST-ED App had comparable test quality (Area under ROC = 0.887) to predict LVO-related AIS to the original FAST-ED (0.889) and RACE (0.883) and was superior to Cincinnati Prehospital Stroke Severity (CPSS), 3-Item Stroke Scale (3-ISS) and National Institute of Health Stroke Scale (NIHSS). A FAST-ED App ⩾ 4 revealed very good accuracy to detect LVO related AIS (sensitivity of 77% and a specificity 87%) with an area under the curve c-statistics of 0.89 (95% CI: 0.87-0.90). In a hypothetical triage model, the number needed to screen in order to avoid one secondary transportation in an urban setting would be five. CONCLUSION: This validation study of a shortened FAST-ED assessment for a smartphone-app guided stroke triage yields good quality to identify patients with LVO.

FAST-ED scale smartphone app-based prediction of large vessel occlusion in suspected stroke by emergency medical service.

BACKGROUND AND PURPOSE: Considering the highly time-dependent therapeutic effect of endovascular treatment in patients with large vessel occlusion-associated acute ischemic stroke, prehospital identification of large vessel occlusion and subsequent triage for direct transport to a comprehensive stroke center offers an intriguing option for optimizing patient pathways. METHODS: This prospective in-field validation study included 200 patients with suspected acute ischemic stroke who were admitted by emergency medical service to a comprehensive stroke center. Ambulances were equipped with smartphones running an app-based Field Assessment Stroke Triage for Emergency Destination scale for transmission prior to admission. The primary measure was the predictive accuracy of the transmitted Field Assessment Stroke Triage for Emergency Destination for large vessel occlusion and the secondary measure the predictive accuracy for endovascular treatment. RESULTS: A Field Assessment Stroke Triage for Emergency Destination ⩾4 revealed very good accuracy to detect large vessel occlusion-related acute ischemic stroke with a sensitivity of 82.4% (95% confidence interval = 65.5-93.2), specificity of 78.3% (95% confidence interval = 71.3-84.3), and an area under the curve c-statistics of 0.89 (95% confidence interval = 0.85-0.94). Field Assessment Stroke Triage for Emergency Destination ⩾4 correctly identified 84% of patients who received endovascular treatment [73.5% specificity (95% confidence interval = 66.4-79.8)] with an area under the curve c-statistics of 0.82 (95% confidence interval = 0.74-0.89). In a hypothetical triage model of an urban setting, one secondary transportation would be avoided with every fifth patient screened. CONCLUSION: A smartphone app-based stroke triage completed by emergency medical service personnel showed adequate quality for the Field Assessment Stroke Triage for Emergency Destination to identify large vessel occlusion-associated acute ischemic stroke. We demonstrate feasibility of the use of a medical messaging service in prehospital stroke care. Based on these first results, a randomized trial evaluating the clinical benefit of such a triage system in an urban setting is currently in preparation.Clinical Trial Registration: https://clinicaltrials.gov Unique identifier: NCT04404504.