True Stroke Research Articles

Abstract TP151: Optimizing Acute Stroke Care Through a Hub-and-Spoke Telestroke Network: Insights from a Large Cohort Analysis

Background: Efficient management of acute ischemic stroke is critical to reducing disability and mortality. The hub-and-spoke telestroke model has been developed to extend specialized stroke care to regions with limited resources, ensuring timely diagnosis and treatment. Objective: To evaluate the effectiveness of a large-scale hub-and-spoke telestroke network in delivering acute stroke care, focusing on the rates of thrombolysis and mechanical thrombectomy, treatment timelines, and patient outcomes. Methods: We conducted a retrospective analysis of 9,702 patients treated within a 38-hospital telestroke network from December 2014 to January 2018. Data collected included patient demographics, stroke characteristics, treatment interventions, and outcomes. Key measures included the proportion of patients receiving intravenous tissue plasminogen activator (IV tPA), mechanical thrombectomy, time from stroke onset to treatment, and rates of complications and discharge outcomes. Results: Of the 9,702 patients included, 83.1% were diagnosed with a true stroke, and the mean NIHSS score on admission was 6.2. IV tPA was recommended for 16.3% of patients, with 61.7% receiving the treatment. Mechanical thrombectomy was performed in 2.3% of cases, with an average procedure duration of 46.2 minutes. The median time from stroke onset to IV tPA administration was 114.2 minutes. Hemorrhagic transformation occurred in 19.4% of patients who received thrombolysis, and the overall mortality rate was 17.4%. The average NIHSS score at discharge improved to 4.4, with 54.9% of patients discharged home. Conclusion: The hub-and-spoke telestroke network demonstrated significant efficacy in delivering timely, specialized stroke care across a large and diverse patient cohort. By reducing treatment delays and optimizing access to advanced interventions, this model has the potential to transform stroke care in underserved regions, reducing both mortality and long-term disability.

Factors affecting emergency medical dispatchers decision making in stroke calls – a qualitative study

ObjectivesEmergency Medical Communication Centers (EMCC) have a key role in the prehospital chain-of-stroke-survival by recognizing stroke patients and reducing prehospital delay. However, studies on EMCC stroke recognition report both substantial undertriage and overtriage. Since mis-triage at the EMCC challenges the whole chain-of-stroke-survival, by occupying limited resources for non-stroke patients or failing to recognize the true stroke patients, there is a need to achieve a more comprehensive understanding of the dispatchers’ routines and experiences. The aim of this study was to explore factors affecting EMCC dispatcher’s decision-making in stroke calls.Materials and methodsA qualitative exploratory study, based on individual semi-structured interviews of 15 medical dispatchers from EMCC Oslo, Norway. Interviews were conducted during August and October 2022 and analyzed using the principles of thematic analysis.ResultsWe identified four themes: [1] Pronounced stroke symptoms are easy to identify [2]. Non-specific neurological symptoms raise suspicion of acute stroke but are difficult to differentiate from other medical conditions [3]. Consistent use of the Criteria Based Dispatch (CBD) protocol may increase EMCC overtriage [4]. Contextual conditions at EMCC can affect dispatchers’ decision-making process and the ability for experiential learning.ConclusionsMedical dispatchers at the EMCC perceive vague and non-specific stroke symptoms, such as dizziness, confusion or altered behaviour, challenging to differentiate from symptoms of other less time-critical medical conditions. They also perceive the current CBD protocol in use as less supportive in assessing such symptoms. High workload and strict EMCC response time interval requirements hinder the gathering of essential patient information and the ability to seek guidance in cases of doubt, potentially exacerbating both EMCC undertriage and overtriage. The absence of feedback loops and other strategies for experiential learning in the EMCC hampers the medical dispatcher’s ability to evaluate their own assessments and improve dispatch accuracy.

Evidence that mitral and/or tricuspid regurgitation diminishes stroke volume increase during exercise

Abstract Background and Purpose The severity of heart failure can be evaluated by peak oxygen consumption (VO2). Cardiac output is one of the major essential factors to determine the VO2. Therefore, cardiac output increases linearly as the exercise intensity increases. However, in mitral regurgitation, effective stroke volume decreases due to some blood flowing back into the left atrium from the left ventricle. This reduction may compromise oxygen delivery to working muscles and diminish oxygen uptake. Peak VO2/HR is known to indicate the stroke volume at the peak exercise, but since c(A-V)O2 difference shows almost a similar change pattern during a ramp protocol, VO2/HR during the load is also reported to be an indicator of stroke volume (SV) at that work rate. However, there are no investigations that have examined the extent to which the increase in cardiac output during stress is affected by the severity of mitral regurgitation. Therefore, we investigated the influence of the degree of regurgitant volume in mitral regurgitation (MR) and tricuspid regurgitation (TR) affects the SV increasing response to exercise load. Additionally, we examined whether blunted SV increase influences on the peak VO2. Methods Among 525 patients who underwent cardiopulmonary exercise test (CPX) at our institution from January 2023 to October 2023, 518 patients (143 females, 375 males, mean age 65.2±15.0 years old) where precise analyses of CPX was possible. CPX was performed using breath-by-breath gas analysis, and an incremental load test (10watts/min) was administered until exhaustion. The rate of increase in VO2/HR per watt during an incremental loading (Δ(VO2/HR)/ΔWR) was used as an indicator of the degree of increase in SV. Typically, SV increases up to 60% of maximum load, around AT, after which it stops increasing and plateaus. Therefore, the slope of Δ(VO2/HR)/ΔWR was examined from the initiation of ramp loading to AT. The degree of reflux was evaluated by echocardiography and classified as none/trivial, mild and moderate/severe. The number of people in each group of None/trivial, mild, moderate/severe was, 392, 83, 30 for MR, and 416, 64, 24 for TR. Δ(VO2/HR)/ΔWR was evaluated for each degree of reflux, using ANOVA to determine whether there was a difference between groups. Results As shown in the Figure1, Δ(VO2/HR)/ΔWR decreased as the reflux flow rate increased for both MR and TR. Concurrently, peak VO2 also decreased in the moderate/severe group compared to the non/trivial-reflux group for both MR and TR (MR: 17.5±5.4 mL/min/kg vs. 14.9±3.5 mL/min/kg, TR: 17.2±5.3 mL/min/kg vs. 13.6±3.8 mL/min/kg). Conclusion The Δ(VO2/HR)/ΔWR obtained through CPX has been shown to be an index that can evaluate the severity of reflux. Additionally, it was also demonstrated that as regurgitation flow increased, true stroke volume decreases, which is correlated with a reduction in peak VO2.

Stroke‐Seg: A deep learning‐based framework for chinese stroke segmentation

AbstractChinese stroke segmentation is a crucial and challenging task for various downstream applications such as font generation, aesthetic evaluation etc. Conventional semantic segmentation techniques typically face difficulties in accurately segmenting strokes, as intersection regions in Chinese characters can belong to multiple strokes simultaneously, and these approaches often lack a holistic understanding of character composition. This paper proposes a character stroke segmentation framework named Stroke‐Seg that integrates with various semantic segmentation architectures, demonstrating adaptability to different backbone networks to tackle the above tasks. A multi‐label output strategy is proposed to effectively classify strokes in intersection areas, overcoming the limitations of traditional semantic segmentation approaches. Additionally, a prior knowledge vector is incorporated into the input layer to provide character‐specific information on stroke composition, enhancing the ability of the framework to precisely identify and segment strokes. The effectiveness of the proposed framework is demonstrated through evaluations of a comprehensive dataset (brush calligraphy stroke segmentation dataset). Evaluations show that the proposed framework significantly improves the capability of semantic segmentation networks, achieving a remarkable improvement of up to 19.9% in the true stroke rate, compared to traditional stroke segmentation techniques. The Stroke‐Seg framework integrated with TransUNet demonstrates its high performance with an impressive 98.2% true stroke rate. Furthermore, the proposed framework combined with FCN still achieves good performance while consuming the least amount of computational resources and memory, demonstrating its potential for lightweight design.

A model of racing kayak surge motion a numerical approach with realistic oscillating propulsion forces

This study presents a novel forward dynamics model of racing kayak surge motion. The model, driven by adjustable oscillating propulsion forces, replicates true paddle stroke forces. It is based on Newton’s second law of motion, with the net force comprising of propulsion force, skin friction drag, wave-making drag, form drag, and air drag. The total mass includes the kayak, paddler, and added mass. The fourth-order Runge–Kutta method is used to solve for speed and distance. The model incorporates a unique hull formulation for wetted surface area estimation, Michell’s integral for wave-making drag, and a log wind profile with allometric scaling for air drag. It accounts for varying stature height, body mass, kayak dimensions, wind speed, and stroke propulsion profiles. The model is a significant advancement in its domain, with broad applicability for the future. It aligns with existing data and analyses, but validation data is limited.

Functional MRI evaluation of hyperbaric oxygen therapy’s effect on hand motor recovery in a chronic post-stroke patient: a case report and physiological discussion

The objective of the case report was to evaluate a specific HBOT protocol as an effective treatment for stroke rehabilitation, specifically improving hand motor function in chronic post-stroke patients. Stroke is the second leading cause of long-term disability worldwide. About 80% of individuals with acute stroke present upper-limb motor impairment, and 50–60% will have persistent disability or weakness at the chronic phase. Impaired upper-limb motor function is highly associated with low self-care ability, limited mobility and poor quality of life. In recent years, there has been evidence of the neuroplasticity effects of HBOT, and HBOT was found to induce neuroplasticity in chronic stages, even years after brain injury. While the healthcare system is primarily focused on teaching patients to live with their impairments, this case report evaluates the effect of a specific hyperbaric oxygen therapy (HBOT) protocol on true stroke rehabilitation, specifically, improving upper-limb function. This case report studied motor task functional MRI (fMRI) activation and resting-state functional connectivity (rsFC) in a 61-year-old right-handed male patient who suffered hemiparesis and physical weakness in the right upper limb two years after his acute insult, pre- and post-treatment of 60 daily HBOT sessions. Motor functions were assessed at baseline and after the treatment using the Fugl–Meyer assessment (FMA) and the handgrip maximum voluntary contraction (MVC). Following the HBOT protocol, the patient’s FMA score improved from 17 (severe impairment) to 31 (moderate impairment), and there was an increase in fMRI activation in both the supplementary motor cortex (SMA) and the premotor cortex (PMA) bilaterally during trials involving the right hand. The lateralization index (LI) decreased from 1 to 0.63, demonstrating the recruitment of the contralesional hemisphere. The region of interest, ROI-to-ROI, analysis revealed increased post-intervention inter-hemispheric connectivity (P = 0.002) and a between-network connectivity increase (z-score: 0.35 ± 0.21 to 0.41 ± 0.21, P < 0.0001). Seed-to-voxel-based rsFC analysis using the right SMA as seed showed increased connectivity to the left posterior parietal cortex, the left primary somatosensory cortex and the premotor cortex. This case report provides additional insights into HBOT-induced brain plasticity and functional improvement in chronic post-stroke patients, and shows HBOT’s potential as an effective, valuable treatment option for those suffering with lingering symptoms after a stroke. This work was conducted by a research team at the Sagol Center for Hyperbaric Medicine and Research at Shamir Medical Center and Tel Aviv University, and published in Frontiers in Neurology. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Wearable and ingestible technology to evaluate and prevent exertional heat illness: A narrative review.

Exertional heat illness remains a constant threat to the athlete, military service member, and laborer. Recent increases in the number and intensity of environmental heat waves places these populations at an ever increasing risk and can be deadly if not recognized and treated rapidly. For this reason, it is extremely important for medical providers to guide athletes, service members, and laborers in the implementation of awareness, education, and measures to reduce or mitigate the risk of exertional heat illness. Within the past 2 decades, a variety of wearable technology options have become commercially available to track an estimation of core temperature, yet questions continue to emerge as to its use, effectiveness, and practicality in athletics, the military, and the workforce. There is a paucity of data on the accuracy of many of these newer devices in the setting of true heat stroke physiology, and it is important to avoid overreliance on new wearable technology. Further research and improvement of this technology are critical to identify accuracy in the diagnosis and prevention of EHI.

Abstract WP313: Towards Molecular Profiling of Transient Ischemic Attack Mimics for Triage

Peripheral blood gene expression profiles can distinguish ischemic stroke from intracerebral hemorrhage and controls. However, it can be difficult to clinically distinguish “mimics” of transient ischemic attacks (TIA) and minor strokes from true TIAs and minor strokes. Even with imaging this can be a challenging differential diagnosis in the ED and other acute settings. Hence, there is a need for defining a molecular profile from blood that could guide triage of TIA mimics to reduce ED burden. This multi-site project collected peripheral blood from the participants and generated gene-level data from RNA sequencing. The cohort was composed of patients with a) TIA mimic presentation (n= 142 TIA mimics: an acute onset of neurological symptoms lasting <24h, that can be explained by some identifiable process other than cerebral ischemia including migraine, seizure, peripheral vestibular disease, brain tumors, syncope, root or peripheral nerve disease, and others); b) patients with transient ischemic attacks (n= 181 TIA: acute onset of neurological symptoms and signs that last <24h with a likely underlying cause of either large vessel atherosclerosis or cardioembolic origin but with a negative brain DWI-MRI); c) controls (n= 172 VRFC: no acute brain event, usually with one or more vascular risk factors including diabetes, hypertension or hypercholesterolemia). Differential expression (DE) analyses (fold change >

Diagnostic accuracy of telestroke consultation: a Louisiana based tele-network experience.

Telestroke has grown significantly since its implementation. Despite growing utilization, there is a paucity of data regarding the diagnostic accuracy of telestroke to distinguish between stroke and its mimics. We aimed to evaluate diagnostic accuracy of telestroke consultations and explore the characteristics of misdiagnosed patients with a focus on stroke mimics. We conducted a retrospective study of all the consultations in our Ochsner Health's TeleStroke program seen between April 2015 and April 2016. Consultations were classified into one of three diagnostic categories: stroke/transient ischemic attack, mimic, and uncertain. Initial telestroke diagnosis was compared with the final diagnosis post review of all emergency department and hospital data. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+) and negative likelihood ratio (LR-) for diagnosis of stroke/TIA versus mimic were calculated. Area under receiver-operating characteristic curve (AUC) analysis to predict true stroke was performed. Bivariate analysis based on the diagnostic categories examined association with sex, age, NIHSS, stroke risk factors, tPA given, bleeding after tPA, symptom onset to last known normal, symptom onset to consult, timing in the day, and consult duration. Logistic regression was performed as indicated by bivariate analysis. Eight hundred and seventy-four telestroke evaluations were included in our analysis. Accurate diagnosis through teleneurological consultation was seen in 85% of which 532 were strokes (true positives) and 170 were mimics (true negatives). Sensitivity, specificity, PPV, NPV were 97.8, 82.5, 93.7 and 93.4%, respectively. LR+ and LR- were 5.6 and 0.03. AUC (95% CI) was 0.9016 (0.8749-0.9283). Stroke mimics were more common with younger age and female gender and in those with less vascular risk factors. LR revealed OR (95% CI) of misdiagnosis for female gender of 1.9 (1.3-2.9). Lower age and lower NIHSS score were other predictors of misdiagnosis. We report high diagnostic accuracy of the Ochsner Telestroke Program in discriminating stroke/TIA and stroke mimics, with slight tendency towards over diagnosis of stroke. Female gender, younger age and lower NIHSS score were associated with misdiagnosis.

Utility of the RIPS Scale and 2CAN Score for In-Hospital Stroke Prediction.

In-hospital strokes are a small but sizeable proportion of all strokes. Identification of in-hospital strokes is confounded by stroke mimics in as many as half of in-patient stroke codes. A quick scoring system based on risk factors and clinical signs during the initial evaluation of a suspected stroke might be helpful to distinguish true strokes from mimics. Two such scoring systems based on ischemic and hemorrhagic risk factors are the risk for in-patient stroke (RIPS) and the 2CAN score. This prospective clinical study was conducted at a quaternary care hospital in Bengaluru, India. All hospitalized patients aged 18 years and above for whom a "stroke code" alert was recorded during the study period of January 2019 to January 2020 were included in the study. A total of 121 in-patient "stroke codes" were documented during the study. Ischemic stroke was the most common etiological diagnosis. A total of 53 patients were diagnosed to have ischemic stroke, 4 had intracerebral hemorrhage, and the rest were mimics. Receiver operative curve analysis was performed and at a cut-off of RIPS ≥3, it predicts stroke with a sensitivity of 77% and a specificity of 73%. At a cut-off of 2CAN ≥3, it predicts stroke with a sensitivity of 67% and a specificity of 80%. RIPS and 2CAN significantly predicted stroke. There was no difference in the use of either RIPS or 2CAN for differentiating stroke from mimics, and hence they may be used interchangeably. They were statistically significant with good sensitivity and specificity, as a screening tool to determine in-patient stroke.

Etiologic reclassification of cryptogenic stroke after implantable cardiac monitoring and computed tomography angiography re-assessment

IntroductionDifferent mechanisms may underlie cryptogenic stroke, including subclinical atrial fibrillation (AF), nonstenotic carotid plaques (NCP), and aortic arch atherosclerosis (AAA). In a cohort of cryptogenic stroke patients, we aimed to: (1) evaluate the prevalence of subclinical AF, NCP, and AAA, and reclassify the etiology accordingly; (2) compare the clinical features of patients with reclassified etiology with those with confirmed cryptogenic stroke.MethodsData of patients hospitalized for cryptogenic stroke between January 2018 and February 2021 were retrospectively analyzed. Patients were included if they received implantable cardiac monitoring (ICM) to detect subclinical AF. Baseline computed tomography angiography (CTA) was re-evaluated to assess NCP and AAA. Since aortic plaques with ulceration/intraluminal thrombus were considered pathogenetic during the initial workup, only patients with milder AAA were included. Stroke etiology was reclassified as “cardioembolic”, “atherosclerotic”, or “mixed” based on the detection of AF and NCP/AAA. Patients with “true cryptogenic” stroke (no AF, ipsilateral NCP, or AAA detected) were compared with those with reclassified etiology.ResultsAmong 63 patients included, 21 (33%) were diagnosed with AF (median follow-up time of 15 months), 12 (19%) had ipsilateral NCP, and 6 (10%) had AAA. Stroke etiology was reclassified in 30 patients (48%): cardioembolic in 14 (22%), atherosclerotic in 9 (14%), and mixed in 7 (11%). Patients with true cryptogenic stroke were younger compared to those with reclassified etiology (p = 0.001).DiscussionOne or more potential covert stroke sources can be recognized in half of the patients with a cryptogenic stroke through long-term cardiac monitoring and focused CTA re-assessment.

Prehospital stroke mimics in the Stockholm Stroke Triage System.

IntroductionIn 2017, Stockholm implemented a new prehospital stroke triage system (SSTS) directing patients with a likely indication for thrombectomy to the regional comprehensive stroke center (CSC) based on symptom severity and teleconsultation with a physician. In Stockholm, 44% of patients with prehospital code stroke have stroke mimics. Inadvertent triage of stroke mimics to the CSC could lead to inappropriate resource utilization.AimsTo compare the characteristics between (1) triage-positive stroke mimics and stroke (TP mimics and TP stroke) and (2) triage-negative stroke mimics and stroke (TN mimics and TN stroke) and to (3) compare the distribution of stroke mimic diagnoses between triage-positive and triage-negative cases.MethodsThis prospective observational study collected data from October 2017 to October 2018, including 2,905 patients with suspected stroke who were transported by code-stroke ambulance to a Stockholm regional hospital. Patients directed to the CSC were defined as triage-positive. Those directed to the nearest stroke center were defined as triage-negative.ResultsCompared to individuals with TP stroke (n = 268), those with TP mimics (n = 55, median 64 vs. 75 years, P < 0.001) were younger and had lower NIHSS score (median 7 vs. 15, P < 0.001). Similarly, those with TN mimics (n = 1,221) were younger than those with TN stroke (n = 1,361, median 73 vs. 78 years, P < 0.001) and had lower NIHSS scores (median 2 vs. 4, P < 0.001). Functional paresis was more common in those with TP mimics than in those with TN mimics, 18/55 (32.7%) vs. 82/1,221 (6.7%), P < 0.001. Systemic infection was less common in those with TP mimics than in those with TN mimics, 1/55 (1.8%) vs. 160/1,221 (13.1%), P < 0.011. There was a trend toward “syncope, hypotension, or other cardiovascular diagnosis” being less common in those with TP mimics than in those with TN mimics, 1/55 (1.8%) vs. 118/1,221 (9.7%), P < 0.055.ConclusionsIn the SSTS, those with triage-positive and triage-negative stroke mimics were younger and had less severe symptoms than patients with stroke. All patients with TP mimics who had hemiparesis but overall exhibited less severe symptoms against true stroke but more severe symptoms than those with TN mimics were triaged to the nearest hospital. Over-triage of functional paresis to the CSC was relatively common. Meanwhile, a large majority of cases with minor symptoms caused by stroke mimics was triaged correctly by the SSTS to the nearest stroke center.

A Case-Control Study of Distinguishing Between Stroke Mimics and True Strokes.

This study was conducted with the primary aim to distinguish patients with a true stroke versus a stroke mimic based on clinical features and imaging. We conducted a retrospective case–control study on 116 adult patients who received alteplase (tPA) to treat acute stroke at our hospital. We further analyzed 79 patients with a normal computed tomography angiography (CTA). Based on their magnetic resonance imaging (MRI) of the brain, they were divided into cases (stroke mimics) and controls (true strokes).Data were collected retrospectively by reviewing individual medical charts on the electronic medical record (EMR), including age, gender, history of stroke, seizure, hypertension, diabetes, atrial fibrillation, hyperlipidemia, presenting NIH Stroke Scale/Score, hemorrhagic conversion, history of migraine, history of depression, sidedness of symptoms and aphasia. Data were categorized to separate those who were later diagnosed to be stroke mimics by being-postictal, encephalopathic, in acute migraine, suffered post-stroke recrudescence (PSR) due to metabolic insult, or had conversion disorder when symptoms could not be attributed to any medical condition or mental illness.Of the 79 study subjects, 48 (60%) were stroke mimics. The mean age of the cohort was 68.67 years, and 46.8% of the study subjects were females. Based on the multivariate logistic regression analysis, factors associated with being a stroke mimic were older age, history of migraine, and a history of prior stroke. In conclusion, increased attention to history and clinical examination as the first step can aid in the proper diagnosis of strokes versus stroke mimics.Identifying stroke mimics early could help expedite hospital workup and prevent inadvertent investigations, reducing hospital occupancy during the ongoing COVID-19 pandemic. We could potentially avoid the administration of tPA to such patients, reducing both the cost and adverse effects of it. Every stroke can cause neurological deficits, but every deficit need not be a stroke.

Abstract WP54: Patient Location Impacts Accuracy Of Inpatient Stroke Alerts

Background: Strokes that occur during inpatient hospitalization require rapid identification and stroke-alert activation from hospital staff in heterogeneous settings, often resulting in overutilization of stroke team resources on stroke mimics. An understanding of the factors that impact accuracy of identification of inpatient strokes would assist in improving care in this population. Methods: This was a retrospective analysis from a single Joint-Commission certified Comprehensive Stroke Center. All patients for whom an inpatient stroke alert was called between 2/1/2019 - 4/30/2021 were included. Metrics captured in our local stroke-alert registry were analyzed, with comparisons made between patients who were determined to have a true stroke versus stroke mimic. Results: Of 705 inpatient alerts, mean patient age was 66 years, 50% were male, 62% occurred in the daytime, and mean NIHSS was 12. The majority of alerts were stroke mimics (76%); most common non-stroke diagnoses were encephalopathy, medical decompensation, and seizure. Among patients with true stroke, 86% were ischemic, with 13 patients receiving thrombolytics and 21 patients undergoing mechanical thrombectomy. One stroke mimic received thrombolytics. Although most alerts originated from medicine units (38%) and floor beds (49%), true stroke was most often diagnosed on cardiology (39%) and hematology/oncology (38%) units, and in the ICU or intermediate care setting (54%). Logistic regression adjusted for age and time of day showed true strokes were significantly associated with male sex, location (stratified by specialty), shorter time to CT completion, and higher initial NIHSS (p&lt;0.05). Conclusions: A majority of inpatient alerts are stroke mimics, particularly on medicine floors. Stroke education could be tailored to staff to incorporate these findings to ensure that stroke patients are not missed, while stroke team resources are not overutilized on mimics.

Clinical Differences Between Stroke and Stroke Mimics in Code Stroke Patients.

BackgroundThe code stroke system is designed to identify stroke patients who may benefit from reperfusion therapy. It is essential for emergency physicians to rapidly distinguish true strokes from stroke mimics to activate code stroke. This study aimed to investigate the clinical and neurological characteristics that can be used to differentiate between stroke and stroke mimics in the emergency department (ED).MethodsWe conducted a retrospective observational study of code stroke patients in the ED from January to December 2019. The baseline characteristics and the clinical and neurological features of stroke mimics were compared with those of strokes.ResultsA total of 409 code stroke patients presented to the ED, and 125 (31%) were diagnosed with stroke mimics. The common stroke mimics were seizures (21.7%), drug toxicity (12.0%), metabolic disorders (11.2%), brain tumors (8.8%), and peripheral vertigo (7.2%). The independent predictors of stroke mimics were psychiatric disorders, dizziness, altered mental status, and seizure-like movements, while current smoking, elevated systolic blood pressure, atrial fibrillation on the initial electrocardiogram, hemiparesis as a symptom, and facial palsy as a sign suggested a stroke. In addition, the likelihood of a stroke in code stroke patients tended to increase as the number of accompanying deficits increased from the following set of seven focal neurological deficits: hemiparesis (or upper limb monoparesis), unilateral limb sensory change, facial palsy, dysarthria, aphasia (or neglect), visual field defect, and oculomotor disorder (P < 0.001).ConclusionSome clinical and neurological characteristics have been identified to help differentiate stroke mimics from true stroke. In particular, the likelihood of stroke tended to increase as the number of accompanying focal neurological deficits increased.

Purines for Rapid Identification of Stroke Mimics (PRISM): study protocol for a diagnostic accuracy study

BackgroundRapid treatment of stroke improves outcomes, but accurate early recognition can be challenging. Between 20 and 40% of patients suspected to have stroke by ambulance and emergency department staff later receive a non-stroke ‘mimic’ diagnosis after stroke specialist investigation. This early diagnostic uncertainty results in displacement of mimic patients from more appropriate services, inappropriate demands on stroke specialist resources and delayed access to specialist therapies for stroke patients. Blood purine concentrations rise rapidly during hypoxic tissue injury, which is a key mechanism of damage during acute stroke but is not typical in mimic conditions. A portable point of care fingerprick test has been developed to measure blood purine concentration which could be used to triage patients experiencing suspected stroke symptoms into those likely to have a non-stroke mimic condition and those likely to have true stroke. This study is evaluating test performance for identification of stroke mimic conditions.MethodsDesign: prospective observational cohort studySetting: regional UK ambulance and acute stroke servicesParticipants: a convenience series of two populations will be tested: adults with a label of suspected stroke assigned (and tested) by attending ambulance personnel and adults with a label of suspected stroke assigned at hospital (who have not been tested by ambulance staff).Index test: SMARTChip Purine assayReference standard tests: expert clinician opinion informed by brain imaging and/or other investigations will assign the following diagnoses which constitute the suspected stroke population: ischaemic stroke, haemorrhagic stroke, TIA and stroke mimic conditions.Sample size: ambulance population (powered for mimic sensitivity) 935 participants; hospital population (powered for mimic specificity) 377 participants.Analyses: area under the receiver operating curve (ROC) and optimal sensitivity, specificity, and negative and positive predictive values for identification of mimic conditions. Optimal threshold for the ambulance population will maximise sensitivity, minimum 80%, and aim to keep specificity above 70%. Optimal threshold for the hospital population will maximise specificity, minimum 80%, and aim to keep sensitivity above 70%.DiscussionThe results from this study will determine how accurately the SMARTChip purine assay test can identify stroke mimic conditions within the suspected stroke population. If acceptable performance is confirmed, deployment of the test in ambulances or emergency departments could enable more appropriate direction of patients to stroke or non-stroke services.Trial registrationRegistered with ISRCTN (identifier: ISRCTN22323981) on 13/02/2019 http://www.isrctn.com/ISRCTN22323981

Abstract P281: Acute Stroke Mimics: Etiological Spectrum and Efficacy of Stroke Assessing Scores

Introduction: Stroke mimics constitute a good number of patients referred as acute strokes within the window period for acute therapies. Proper triaging can avoid unnecessary imaging and even thrombolytic therapies in these patients. This study looked at etiological spectrum of acute stroke mimics presenting within the 4.5 hours therapeutic window. We also evaluated the FAST (Face-Arm-Speech-Time), BEFAST (Balance -Eyes-Face-Arm-Speech-Time) and the ROSIER (Recognition of Stroke in the Emergency Room) tools in picking true strokes. Methods: A prospective observational cohort study over a 2- year period; A descriptive analysis of various etiologies presenting as acute stroke was done. The presenting symptoms, signs and the diagnostic value of the FAST, BEFAST, and the ROSIER Scores in both the stroke mimics and true strokes were noted and the sensitivity and specificity for picking up the stroke mimics were calculated. Student’s t test, univariate analysis and multivariate logistic regression analysis were done. Diagnosis of stroke was confirmed by MRI. Results: After initial screening by Neurologists, stroke mimics constituted 328/1635 (20%) of referrals for acute stroke. Focal and generalized seizures with transient weakness and peripheral vertigo were the most common acute stroke mimics; followed by metabolic causes and psychiatric disorders. Females were more in the stroke mimic group (p = 0.02). Ischemic heart disease and atherosclerotic risk factors (except diabetes mellitus) were significantly higher among true strokes. 4 (1.2%) of the stroke mimics were treated with IV thrombolysis. Diagnostic accuracy for different stroke differentiating tools were: FAST (Sensitivity 85,9% specificity 52.8% Odds 6.8), BEFAST (Sensitivity 97.0% specificity 31.4% Odds 14.9) And ROSIER Scale (Sensitivity 85.7% specificity 59.4% Odds 8.7%). In Conclusion, Stroke mimics can constitute up to 20% of cases evaluated as strokes. None of the triaging tools appear to have enough accuracy. A proper history and clinical examination should be given priority over fixed protocols whenever acute stroke mimic are suspected, especially before administering acute costly interventions. Auditing stroke mimics is important to improve acute stroke pathways.

Abstract P689: Do Cyclic Patterns of Stroke Code Activation Occur in a Comprehensive Stroke Center?

Background: The effects of circadian rhythm on stroke can include increases in morning heart rate, blood pressure, catecholamines, platelet aggregation, and hypercoagulability and might correlate with higher numbers of morning strokes. We assessed time of day and frequency of stroke code activation for a potential role of circadian rhythm in stroke risk. Methods: A retrospective analysis of prospectively collected data from an IRB approved stroke registry, from July 2004 to July 2020, was performed. Codes were included where stroke codes were activated with last known well (LKW) &lt;6 hours to limit the effect of wake-up strokes and equalize changing practice patterns over time. Subjects were divided into four epochs based on code activation: Night (00:00-05:59), Morning (06:00-11:59), Afternoon (12:00-17:59), and Evening (18:00-23:59). Confirmed diagnosis of stroke, baseline blood pressure (SBP &amp; DBP), heart rate (HR), and PTT were compared. Chi squared was used to compare categorical data and t test for continuous. Results: A total of 5,366 subjects were identified. Stroke code activations differed across epochs (Night n=312, 5.81%; Morning n=1439, 26.82%; Afternoon n=2207, 41.13%; Evening n=1408, 26.24%: p&lt;0.0001). In the subset analysis of true strokes, activations also differed across epochs (Night n=125, 5.26%; Morning n= 831, 34.95%; Afternoon n=934, 39.28%; Evening n=488, 20.52%: p&lt;0.0001). Overall, SBP was different with Evening highest and Morning lowest (x 151.6, x 148.2;p=0.01). Overall DBP showed Night highest and Afternoon lowest (x 83.9, x 81;p=0.002). Heart rate showed Night highest and Morning lowest (x 84.9, x 81.6;p=0.002). Conclusions: This study found that most stroke code activations occur in Afternoons at this CSC. This may be due to patient level characteristics, bystander availability, or other factors. Future studies should assess multi-center data and include other circadian rhythm biomarkers.

Metabolically Active Subacute Infarct Masquerading as Metastasis: A Finding not to be overlooked in Asymptomatic Oncology Patients.

A 50-year-old man with carcinoma of the right buccal mucosa underwent staging whole-body 18F-fluorodeoxyglucose positron emission tomography–computed tomography, which revealed a hypermetabolic heterogeneously enhancing lobulated primary lesion in the right buccal region and an incidental finding of subacute stroke. The case highlights the importance of discriminating brain neoplasms mimicking stroke from true ischemic stroke, which is crucial for appropriate management of patients in an oncology setting.

Acute Stroke Mimics: Etiological Spectrum and Efficacy of FAST, BE FAST, and the ROSIER Scores

Background and Purpose: Stroke mimics constitute a good number of patients referred as acute strokes within the window period for acute therapies. Proper triaging can avoid unnecessary imaging and even thrombolytic therapies in these patients. This study looked at the etiological spectrum of acute stroke mimics presenting within the 4.5 hours therapeutic window. We also evaluated the FAST, BE FAST, and the ROSIER tools in picking true strokes. Methods: Prospective study conducted over a 2-year period. Results: Acute stroke mimics constituted 328/1635 (20%) of referrals for acute stroke after screening by the neurology stroke team. Focal and generalized seizures with transient weakness and peripheral vertigo were the commonest acute stroke mimics; followed by metabolic causes and psychiatric disorders. Females were more in the stroke mimic group ( P = .02). Ischemic heart disease and atherosclerotic risk factors (except diabetes mellitus) were significantly higher among true strokes. In total, 4 (1.2%) of the stroke mimics were treated with IV thrombolysis. Diagnostic accuracy for different stroke differentiating tools are as follows: FAST (sensitivity 85.9%, specificity 52.8%, odds 6.8), BE FAST (sensitivity 97.0%, specificity 31.4%, odds 14.9), and ROSIER scale (sensitivity 85.7%, specificity 59.4%, odds 8.7%). Conclusions: Acute stroke mimics can constitute up to 20% of cases evaluated as acute strokes by neurology stroke teams. None of the triaging tools appear to have enough accuracy. A proper history and clinical examination should be given priority over fixed protocols whenever acute stroke mimic are suspected especially before administering acute costly interventions. Auditing stroke mimics is important to improve acute stroke pathways.