Common Stroke Mimics Research Articles

Patient-reported symptoms and admission pathways in stroke mimics versus confirmed stroke or transient ischaemic attack: a cross-sectional observational study

ObjectivesTo determine patient-reported symptoms and clinical factors associated with mimics and differences in health-seeking behaviour versus stroke.DesignThis is a post-hoc analysis of a cross-sectional survey of interviews on patient-reported factors...

Abstract TP45: Demonstration Of High Diagnostic Accuracy Of Cerebral Ischemia In A Large Academic Hub And Spoke Telestroke Network

Introduction: Telestroke facilitates emergent assessment of patients with suspected acute ischemic stroke (AIS) to identify candidates for acute interventions. The diagnostic accuracy of the telestroke consultation of a large academic hub and spoke telemedicine network has yet to be investigated. The goal of our study is to determine the diagnostic accuracy of the initial telestroke consultation. Methods: This is an IRB-exempt retrospective study including all patients evaluated for cerebral ischemia via video telestroke consultation in a large academic hub and spoke telemedicine network from 2019 to 2020. Detailed chart review was conducted to identify initial suspected diagnosis and final diagnosis. Cerebral ischemia was defined as AIS and transient ischemic attack (TIA). All other diagnoses were defined as stroke mimics. Data was organized into continuous and categorical variables. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, area under the curve (AUC) and likelihood ratio (LR+) for the initial telestroke consultation diagnosis were calculated while using the final diagnosis as the gold standard diagnosis. Results: A total of 1043 patients met inclusion criteria. Final diagnosis of cerebral ischemia was made in 63.5% of all patients (539/1043 with AIS,123/1043 with TIA). Stroke mimic was diagnosed in 36.5% patients (381/1043). The sensitivity and specificity of telestroke evaluation for diagnosis of cerebral ischemia were 97.1% and 81.4%, respectively. PPV was 90.1%, and NPV was 94.2%. Overall diagnostic accuracy was 91.4% with a LR+ of 5.21 and AUC of 0.89. The most common stroke mimics were metabolic encephalopathy (13.7%, 52/381), migraine (10.8%, 41/381) and seizure (10.5%, 40/381). Conclusions: This study highlights the high diagnostic accuracy of telestroke providers to diagnose cerebral ischemia and stroke mimic in a large academic hub and spoke network. Further research is needed to investigate methods to improve our diagnostic accuracy further, as well as explore the application of tele-neurology in the non-stroke setting.

Prehospital Stroke Care, Paramedic Training Needs, and Hospital-Directed Feedback in Lithuania.

Background: Emergency medical services (EMS) are the first health care contact for the majority of stroke patients. However, there is a lack of data on the current paramedics’ hospital-directed feedback and training needs across different health care settings. We aimed to evaluate paramedics’ prehospital stroke care knowledge, training needs, and current status of feedback on suspected stroke patients. Methods: We surveyed paramedics from the Vilnius region from September to November 2019 and compared the answers between the city and the district agencies. The questionnaire content included questions on paramedics’ demographic characteristics, prehospital stroke care self-assessment, knowledge on stroke mimics, stroke training needs, and the importance of hospital-directed feedback on suspected stroke patients. Results: A total number of 161 paramedics (or 49.4% of all paramedics from our stroke care network) were surveyed, with more district paramedics rating their prehospital stroke care knowledge as inadequate (44.8% (95% confidence interval (CI) 32.8–57.6) vs. 28.1% (95% CI 20.1–27.8), p = 0.028). In addition, more district paramedics indicated a need for additional stroke training (83.1% (95% CI 71.5–90.5) vs. 69.8% (60.0–78.1), p = 0.043). However, respondents reported being the most confident while dealing with stroke (71.3%, 95% CI 63.8–77.7) compared to other time-critical conditions (p < 0.001). Vertigo (60.8%, 95% CI 53.0–68.0), brain tumors (56.3%, 95% CI 48.5–63.8), and seizures (54.4%, 95% CI 46.7–62.0) were indicated as the most common stroke mimics. Only 6.2% (95% CI 3.4–11.1) of respondents received formal feedback on the outcome of suspected stroke patients brought to the emergency department. Conclusions: A high proportion of paramedics self-perceive having inadequate stroke knowledge and an urgent need for further stroke training. The EMS staff indicate receiving insufficient feedback on suspected stroke patients, even though its usefulness is perceived as paramount.

Abstract TP170: Pediatric Acute Stroke Team Activation: Differentiating Stroke From Mimics

Acute pediatric stroke is a medical emergency requiring prompt recognition and treatment because quicker treatment improves neurologic outcomes and reduces excess resource usage on stroke mimics (non-stroke diagnoses). There is a clear need to better differentiate between strokes and their mimics. We performed a single center retrospective cohort study using data from March 1, 2017 to December 31, 2020. We included pediatric patients (&gt; 1m to &lt; 18y) evaluated in the tertiary children’s hospital ED for a stroke team activation. We compared clinical features for patients with stroke and those with a stroke mimic. Of 179 children included in the study (55% female, mean age 11.2y, SD 5.7y), 38 children (21% of total patients, 50% female, mean age 10.5 SD, 6.2 years) were diagnosed with stroke. Strokes included acute ischemic stroke (AIS) (73.7%), hemorrhagic stroke (HS) (18.4%), and cerebral venous sinus thrombosis (CVST) (10.5%). The most common stroke mimics were seizure (14.5%), headache (10.5%), Bell's palsy (5.6%), and conversion disorder (2.7%). Compared to mimics, stroke patients were less likely to have a history of neurosurgery (16.3% mimic vs 2.6% stroke, p=0.028) and more likely to have altered level of alertness (7.7% vs 18.4%, p=0.001), abnormal coordination (15.7% vs 36.4%, p=0.036), abnormal muscle strength (33.1% vs 57.9%, p=0.005) and abnormal reflexes (18.9% vs 43.8%, p=0.018). Of note, there were no significant differences in stroke and mimics for: age, sex, race, ethnicity, basic metabolic panel or CBC, and time from last seen well. Differentiating between strokes and mimics remains difficult without comprehensive diagnostic testing. Our study found that stroke patients are more likely present with altered level of alertness as well as abnormal coordination, muscle strength, and reflexes.

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.

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.

A novel computed tomography perfusion-based quantitative tool for evaluation of perfusional abnormalities in migrainous aura stroke mimic.

Migrainous aura (MA) represents the third most common stroke mimic (SM). Advanced neuroimaging is pivotal in the assessment of patients with focal neurological acute symptoms. We investigated brain perfusion alterations in MA-SM patients using a novel CT perfusion (CTP)-based quantitative approach in order to improve differential diagnosis between MA and acute stroke. We processed and analysed the clinical and neuroimaging CTP data, acquired within 4.5 h from symptom onset, of patients with acute focal neurological symptoms receiving a final diagnosis of MA. The differences between ROI, compatible with MA symptoms, and contralateral side were automatically estimated in terms of asymmetry index (AI%) by the newly developed tool for mean transit time (MTT), CBF, and cerebral blood volume (CBV) CTP parameters. The AI% ≥ 10% was considered significant. Out of 923 admitted patients, 14 patients with MA were included. In 13 out of 14 cases, a significant pattern of hypoperfusion was observed by quantitative analysis in at least one of the CTP maps. In 7 patients, all three CTP maps were significantly altered. In particular, MTT-AI% increased in 11 (79%) cases, while CBF-AI% and CBV-AI% decreased in 12 (86%) and in 9 (64%) patients, respectively. All CBV values were above ischemic stroke core threshold and all MTT-AI were below ischemic penumbra threshold. Our data suggest that a novel CTP-quantitative approach may detect during MA a moderate hypoperfusion pattern in the cerebral regions compatible with aura symptoms. The use of this novel tool could support differential diagnosis between MA and acute stroke.

Functional Neurological Disorder: A Common and Treatable Stroke Mimic.

Functional Neurological Disorder: A Common and Treatable Stroke Mimic.

Abstract TP244: Predictive Scoring System to Differentiate Acute Ischemic Stroke From Stroke Mimic During Code Stroke Evaluation

Background: Migraine, seizure and toxic metabolic encephalopathy are common stroke mimics (SM) during code stroke (CS) evaluation and up to 30% of patients treated with IV tPA are found to have SM. An ideal way to differentiate SM from acute ischemic stroke (AIS) is through history and clinical examination in conjunction with MRI brain. Quick identification of a set of clinical characteristics predictive of SM may be helpful to prevent unnecessary IV thrombolysis. This study aimed to develop and evaluate effectiveness of a predictive scoring system to differentiate AIS from SM. Methods: The study population included 508 patients who received IV tPA from Jan 2013-Dec 2016 at a large comprehensive stroke center. Sixty clinical characteristics were reviewed and 27 were chosen for prediction analysis based on univariate ANOVA F-test. A prediction model is proposed by multivariate logistic regression with step wise selection of variables with the variable entry and stay threshold of p value 0.2 and 0.05 respectively to develop a predictive score. Results: Our scoring system consists of 7 clinical characteristics which are easily assessable during “CS” with yes and no answers. Each clinical variable has score weightage based on strength of statistical association with final diagnosis AIS Vs SM. Score is composed of : seizure at onset (score yes: -1.8, no:0), headache (yes: -2.3, no:0), history of migraine (yes: -1.7, no:0) , encephalopathy (yes: -1.2, no:0), atrial-fibrillation (yes: 1.3, no:0), NIHSS (0.1 per unit) and localizable symptoms (yes : 3.3, no: 0). Area under receiver operative characteristic (ROC) curve was 0.91 and a score &gt;3.4 identified AIS with a sensitivity of 88.3% and specificity of 82.1%. Conclusion: Our study found that clinical characteristics of acute presentation were more helpful than conventional vascular risk factors history to differentiate AIS from SM. Our predictive score is reliable to differentiate AIS from SM and is intended to help clinicians identify SM using quick and simple clinical characteristics. Prospective validation of the score is needed.

Adult Migraine Hospital Admission Trends in Finland: A Nationwide Registry Study.

Population-level data on migraine hospital admission trends are unavailable. Changes in stroke care may have influenced these, since migraine is one of the most common stroke mimics. In this study, all hospital admissions on neurological, internal medicine, and pediatric wards in Finland with migraine as the primary diagnosis for persons at least 16 years of age in 2004–2014 were studied, resulting in an analysis of 6195 individuals with 7764 migraine discharges. The number of discharges increased by 4.2% annually (p = 0.000084), with no change in age of the admitted patients. Comorbidity burden was low but increased during the study period (p < 0.0001). The frequency of common vascular risk factors as comorbidities increased by 11–19% annually. Admission duration shortened by 2% annually (p < 0.0001). An intravenous thrombolysis was given in four admissions. It seems that migraine hospital admissions have become more frequent and the patients more often have cardiovascular risk factors, suggesting increased awareness and more aggressive acute evaluation of suspected stroke as the cause.

Stroke Mimics: An Important Source of Bias in Acute Ischemic Stroke Research

Study Objective: Stroke mimics may be difficult distinguish from acute ischemic strokes and are often treated with alteplase though not by intent. We report the characteristics, frequency, and outcomes of stroke mimics treated at our institution. Using our data, we then explore how the inclusion of stroke mimics in stroke outcomes research may be an important source of bias. Methods: We retrospectively identified all patients treated with alteplase in our emergency department from August 2013 to December 2017 for suspected acute ischemic stroke. We collected the following variables: gender, age, risk factors (hypertension, diabetes, and atrial fibrillation), admission glucose, admission National Institute of Health Stroke Scale, admission mean arterial pressure, onset-to-treatment time, adverse events, discharge diagnosis, length of stay, discharge NIHSS, discharge destination, and 3 month modified Rankin score. Results: One hundred and eighteen patients were treated with alteplase for suspected acute ischemic stroke of which 33 (27.9%) were stroke mimics. Compared to ischemic strokes, stroke mimics were younger (median age 53 versus 69; P < .0003); were less likely to have vascular risk factors (hypertension [51.5% versus 78.8%; P < .005] diabetes (9.1% versus 32.9%; P < .007), and atrial fibrillation (3.0% versus 23.5%; P < .006). The most common stroke mimic was transient ischemic attack (33.3%). Stroke mimics were significantly more likely to be discharged home (75.8% versus 41.2%; P < .002). Outcomes unadjusted for stroke mimics led to artificial inflation of a favorable discharge destination. Conclusions: Inclusion of stroke mimics led to an artificial inflation of a favorable discharge destination for our entire cohort. Our study highlights the potential for bias in reporting favorable outcomes if appropriate adjustment accounting for stroke mimics does not occur.

Identifying and differentiating stroke and stroke mimics.

Stroke mimics are common differential diagnoses of stroke. This article describes common stroke mimics and their presentations. It provides nurses with an overview of how to distinguish stroke mimics from a stroke, and practical information on triaging and diagnosing stroke and stroke mimics in the clinical setting. Stroke and stroke mimics have several similarities and several important differences. A comprehensive patient history, clinical examination, use of assessment tools and the results of medical imaging can guide nurses to differentiate stroke from a stroke mimic.

Abstract TMP82: Rates and Predictors of Stroke Mimics Among In-Hospital Code Stroke Activations

Introduction: In-hospital strokes have a different pattern of risk factors, etiologies, and mimics than strokes that are initially evaluated in the Emergency Department. In-hospital stroke patients often have multiple confounding comorbidities which may provide alternative explanations for suspected stroke symptoms. Objective: To characterize strokes vs. stroke mimics among in-hospital Code Stroke activations. Methods: We identified all adults with an in-hospital Code Stroke activation between September 2014 and February 2018 at a single academic medical center (660 beds) and abstracted the reason for Code Stroke activation, comorbidities, primary inpatient service, patient location, NIHSS, and final diagnosis from comprehensive electronic health records. Univariate and multivariate logistic regression were used to assess the association between clinical variables and stroke mimics. Results: Of 461 in-hospital Code Stroke activations, the final diagnoses were 110 (24%) ischemic stroke or TIA, 35 (7.5%) intracranial hemorrhage, and 316 (68.5%) stroke mimics. Of the 85 patients with a final diagnosis of ischemic stroke, 9 (8%) received tPA and 2 underwent embolectomy (1.8%). The most common reason for Code Stroke activation was altered mental status (48%). Altered mental status (OR 0.20, 95% CI 0.10-0.39) and previously-known CNS tumor (OR 0.18, CI 0.05-0.69) were least likely to be associated with a final diagnosis of stroke. The most common stroke mimics were toxic/metabolic encephalopathy, seizure, and delirium. Limb weakness (OR 6.93, CI 3.86-12.7), recent cardiac/vascular procedure (OR 5.03, CI 1.92-8.89) and NIHSS (OR 1.09 per point, CI 1.05-1.13) were predictive of stroke in multivariate analysis. Conclusions: A majority of in-hospital Code Stroke activations are for stroke mimics. Altered mental status was the most common reason for Code Stroke activation, yet was least likely to be associated with a final diagnosis of stroke. While rapid recognition of stroke symptoms and timely Code Stroke activations are critical to maximizing opportunities to apply acute interventions, variability in the reasons for Code Stroke activation particularly for undifferentiated altered mental status may be a target for future optimization.

Abstract TP264: Telestroke Diagnosis of Conversion Disorder

Conversion Disorder (CD) is a common stroke mimic of ischemic stroke (IS) or TIA. Although studies comparing stroke mimics with IS or TIA exist, there is a paucity of data comparing demographic and clinical features of CD and IS/TIA and evaluating diagnostic accuracy of CD via telemedicine. Methods: We retrospectively reviewed telestroke consultations at our center between April 2015 and July 2016. All patients were assessed remotely using telestroke service by physicians at the Ochsner Neuroscience Institute. Consultations were classified into one of 2 diagnostic categories: IS/TIA and CD; other stroke mimics were excluded. Initial diagnosis was compared with final diagnosis, determined after review of additional emergency department testing or hospital admission. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for diagnosis of CD were calculated. Bivariate analysis based on the diagnostic categories was used to examine association with sex, age, NIH Stroke Scale (NIHSS), stroke risk factors (CAD, DM, HLD, HTN, history of stroke/TIA, smoking, atrial fibrillation (AFIB)), TPA given, bleeding after TPA, and consult duration. Area under receiver-operating curve (AUC) for telestroke diagnostic accuracy of CD was calculated. Results: 616 telestroke evaluations were included in our analysis. Sensitivity, specificity, NPV, PPV of CD diagnosis were 0.82, 0.998, 0.985 and 0.976, respectively. Variables that reached statistical significance between CD and IS/TIA were female gender (0.0006), age (&lt;0.0001), DM (0.0252), HTN (0.0004), AFIB (&lt;0.0001), TPA given (&lt;0.0001), and median consult duration (0.0175). Median consult duration (min) of misdiagnosed cases was 27.5 (18.5, 32) and that of correctly diagnosed cases was 10.5 (7, 16). Adjusted AUC (95% CI) was 0.92 (0.87, 0.97). Conclusions: Our unadjusted telemedicine CD diagnostic accuracy is 0.98. In the bivariate analysis CD patients are more likely to be female, younger, and have no history of DM, HTN or AFIB compared with IS/TIA patients. CD patients received shorter consult time compared with IS/TIA patients, and received less TPA. CD misdiagnosed cases had a longer median consultation time than correctly diagnosed cases.

Errors in the Diagnosis of Stroke-Tales of Common Stroke Mimics and Strokes in Hiding.

Introduction:Stroke mimics are some of the common causes of misdiagnosis of stroke, with an attendant surfeit of finances and resources.Aim:We attempt to discuss some of the common neurological conditions mimicking stroke in the emergency.Methods:We reviewed the articles in English discussing stroke mimics in the last 5 years of publication.Purpose of the Review:We discuss the most common causes of stroke mimics encountered in neurological practice. In this short communication, we shall focus on the discussion of the diagnostic pitfalls and clinical clues that will help distinguish mimics from a true stroke.

Ischaemic stroke may symptomatically manifest as migraine aura

Migraine aura is a common stroke mimic. We hypothesised that some patients with typical migraine aura symptoms might have embolic stroke detected as the precipitant. We identified fourteen patients who presented with symptoms consistent with a clinical diagnosis of migraine aura, but demonstrated subsequent evidence of acute infarction on magnetic resonance imaging (MRI). In all patients, migraine aura symptoms were not directly attributable to the vascular lesion on MRI. 50% of patients were classified as having an embolic stroke of undetermined source. Of these, a patent foramen ovale was identified in 4/5 of those who underwent transoesophageal echocardiogram, with large right-to-left shunt demonstrated in three. The results from our cohort suggest that migraine aura can be the presenting feature of acute ischaemic stroke, with local ischaemia presumably triggering a widely migrating cortical wave of spreading depolarization.

When migraine mimics stroke: A systematic review.

Migraine with aura may mimic an acute ischemic stroke, so that an improper administration of thrombolytic treatment can expose migrainous patients to severe adverse effects. This systematic review quantifies the relevance of migraine with aura among stroke mimics, checking for thrombolysis' safety in these patients. We reviewed the literature after 1995, distinguishing from studies dealing with stroke mimics treated with systemic thrombolysis and those who were not treated with systemic thrombolysis. Migraine with aura is responsible for 1.79% (CI 95% 0.82-3.79%) of all the emergency Stroke Unit evaluations and it represents 12.24% (CI 95% 6.34-22.31%) of stroke mimics in the group not treated with systemic thrombolysis. 6.65% (CI 95% 4.32-9.78%) of systemic thrombolysis administrations are performed in patients without an acute ischemic stroke. Migraine with aura is responsible for 17.91% of these (CI 95% 13.29-23.71%). The reported rate of adverse events seems extremely low (0.01%). Migraine with aura is the third most common stroke mimic, following seizures and psychiatric disorders; it is responsible for about 18% of all improper thrombolytic treatments. Despite the absence of strong supporting data, thrombolysis in migraine with aura seems to be a procedure with an extremely low risk of adverse events.

Pediatric Stroke and Its Mimics: Limitations of a Pediatric Stroke Clinical Pathway

BackgroundAcute stroke protocols improve delivery of care but it is unclear whether these resource intensive protocols are able to differentiate stroke from mimics in children. The aim of this study is to describe our institution's experience with stroke mimics identified through our pediatric stroke clinical pathway (PSCP). MethodsThe PSCP was implemented in our level 1 pediatric emergency department in June 2014 for children aged one month to 18 years. For patients managed using the PSCP from June 2014 to December 2016, demographic and clinical data were compared for patients diagnosed with stroke or a stroke mimic. ResultsA total of 59 children were evaluated with the PSCP. Fourteen children were identified as having a stroke and 45 children had stroke mimics. The most common stroke mimics were functional neurological disorders (20.0%), transient neurological deficits (17.8%), migraine (15.6%), and seizure (11.1%). Patient demographics and time to neuroimaging did not differ between patients with and without stroke. Vomiting was commonly reported by patients with stroke (odds ratio: 4.00, 95% confidence interval: 1.12 to 14.35), whereas weakness was not (odds ratio: 0.7, 95% confidence interval: 0.07 to 0.90), but the physical examination did not differ between patients with and without stroke. ConclusionsThe PSCP ensures timely evaluation of patients presenting with neurological deficits but fails to reliably differentiate between patients with stroke and patients with stroke mimics. Further multicentered studies are needed to develop a “stroke screen” that reliably distinguishes pediatric stroke from its mimics.

Mimics and chameleons in stroke

Ischaemic stroke is a treatable medical emergency. In an era of time-dependent reperfusion techniques, it is crucial that an accurate and prompt diagnosis is made. Approximately 30% of patients admitted to hyperacute stroke units are subsequently found not to have a final diagnosis of acute stroke although some of these patients do have incidental or previously symptomatic cerebrovascular disease. These patients do not benefit from thrombolysis and may require the input of other specialists or treatments. Meanwhile, a proportion of patients with acute stroke have unusual presentations and are sometimes initially admitted to general medical admissions units prior to accessing stroke unit care. It is important that atypical presentations of stroke are recognised so that patients are not denied the benefits of stroke unit care and secondary prevention. This article describes some characteristics of common stroke mimics and chameleons, considers how to avoid diagnostic mistakes and discusses the contributory role of imaging.

Abstract WMP110: Differentiating Childhood Arterial Ischemic Stroke From Migraine in the Pediatric Emergency Department

Objective: Migraine, a typically benign disorder, is the most common stroke mimic in children presenting with brain attacks. We aimed to identify clinical features which discriminate childhood arterial ischaemic stroke (AIS) from migraine. Methods: Fifty-five consecutive children with AIS, presenting to a tertiary pediatric emergency department (ED), prospectively/retrospectively recruited from 2003-2010, were compared to 84 children with migraine, prospectively recruited from 2009-2010. Results: Health professional referral, (odds ratio (OR), 5.71, 95% confidence intervals 2.54-12.81), ambulance transport (OR 2.95, 1.45-5.97), high triage category assignment (OR 2.41, 1.06-5.49), sudden onset (OR 2.74, 1.18-6.39), symptoms of focal weakness (OR 6.96, 3.24-14.93), seizures (OR 7.44, 1.99-27.81), speech disturbance (OR 3.06, 1.48-6.32), and ataxia (OR 4.88, 1.63-14.65) were significantly associated with increased odds of AIS diagnosis. Signs of face (OR 155.37, 20.03-1205.33), arm (OR 15.58, 6.41-37.84), or leg weakness (OR 15.40, 5.75-41.27), inability to walk (OR 14.18, 3.07-65.41), dysarthria (OR 47.21, 6.07-367.13), dysphasia (OR 12.76, 1.52-106.97) and altered consciousness (OR 2.45, 1.03-5.85) were also significantly associated with increased odds of AIS diagnosis, In contrast, vomiting (OR 0.23, 0.10-0.53), visual symptoms (OR 0.24, 0.10-0.57), other symptoms (OR 0.06, 0.01-0.48) and absence of neurological signs on ED physician assessment (OR 0.05, 0.01-0.17) were associated with decreased odds of AIS diagnosis. Conclusion: Differing presenting symptoms and signs allow discrimination of childhood AIS from migraine. These findings can inform decisions about urgency and type of diagnostic neuroimaging in the ED for children presenting with brain attack symptoms.