Acute Stroke Mimics Research Articles

Case report: Ethylene glycol intoxication presenting as a mimic of acute stroke: a report of three cases

Stroke is a major cause of death and disability presenting with acute focal neurological symptoms of vascular origin. Several other disorders may cause symptoms similar to a stroke, referred to as stroke mimics. The misdiagnosis of stroke mimics may lead to potentially harmful treatments, including thrombolysis. Intoxication is a rare, but possible, cause of stroke mimic. We present three cases of ethylene glycol poisoning presenting as an acute stroke mimic within the time window of thrombolytic therapy. Two of three patients (a 54-year-old male and a 78-year-old male) had dysarthria, nystagmus, and truncal ataxia on admission. The third patient with a history of chronic alcoholism presented after an epileptic seizure with mixed aphasia and confusion. Non-contrast cerebral computed tomography and computed tomography angiography were negative in all three cases. As stroke could not be excluded in any of the patients, thrombolysis was performed. However, after some hours, two of the three patients developed agitation, somnolence, and hyperventilation. One patient's consciousness deteriorated rapidly, and he became comatose and tetraplegic. A blood gas analysis showed acidosis in two of the three patients, and toxicological screening revealed ethylene glycol intoxication in all three cases. Due to the appropriate treatment, two of the three patients became symptom-free; however, one of the three patients died. Our cases show that ethylene glycol intoxication in its early phase may mimic acute stroke, resulting in unnecessary thrombolytic therapy. Symptoms not characteristic of a stroke, such as hyperventilation, agitation, and disturbance of consciousness, may appear later and warn of intoxication. The final diagnosis of ethylene glycol intoxication can be established by severe metabolic acidosis and toxicological screening. Close monitoring of symptoms might contribute to the early recognition of ethylene glycol intoxication and its effective treatment.

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 developing brain abscess as acute stroke mimic: presentation of case and review of literature

Whether brain abscess is a cause, or a complication of stroke has been a question that elicited differing opinions. We report a case of a child who initially presented with hemiparesis and seizures. Initial brain tomography did not show hemorrhage or infarction. He was managed as a case of childhood stroke. The neurologic manifestations gradually improved until the 17th day of hospitalization when regression of the motor strength and anisocoria occurred. A repeat brain tomography showed multiple masses and vasogenic edema consistent with brain abscess.

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.

Characteristics of Perfusion Computed Tomography Imaging in Patients with Seizures Mimicking Acute Stroke

Introduction: Seizures as acute stroke mimics are a diagnostic challenge. Objective: The aim of the study was to characterize the perfusion patterns on perfusion computed tomography (PCT) in patients with seizures masquerading as acute stroke. Methods: We conducted a study on patients with acute seizures as stroke mimics. The inclusion criteria for this study were patients (1) initially presenting with stroke-like symptoms but finally diagnosed to have seizures and (2) with PCT performed within 72 h of seizures. The PCT of seizure patients (n = 27) was compared with that of revascularized stroke patients (n = 20) as the control group. Results: Among the 27 patients with seizures as stroke mimics, 70.4% (n = 19) showed characteristic PCT findings compared with the revascularized stroke patients, which were as follows: (1) multi-territorial cortical hyperperfusion {(73.7% [14/19] vs. 0% [0/20], p = 0.002), sensitivity of 73.7%, negative predictive value (NPV) of 80%}, (2) involvement of the ipsilateral thalamus {(57.9% [11/19] vs. 0% [0/20], p = 0.007), sensitivity of 57.9%, NPV of 71.4%}, and (3) reduced perfusion time {(84.2% [16/19] vs. 0% [0/20], p = 0.001), sensitivity of 84.2%, NPV of 87%}. These 3 findings had 100% specificity and positive predictive value in predicting patients with acute seizures in comparison with reperfused stroke patients. Older age was strongly associated with abnormal perfusion changes (p = 0.038), with a mean age of 66.8 ± 14.5 years versus 49.2 ± 27.4 years (in seizure patients with normal perfusion scan). Conclusions: PCT is a reliable tool to differentiate acute seizures from acute stroke in the emergency setting.

Shifts in Leukocyte Counts Drive the Differential Expression of Transcriptional Stroke Biomarkers in Whole Blood.

Our group recently identified a panel of ten genes whose RNA expression levels in whole blood have utility for detection of stroke. The purpose of this study was to determine the mechanisms by which these genes become differentially expressed during stroke pathology. First, we assessed the transcriptional distribution of the ten genes across the peripheral immune system by measuring their expression levels on isolated neutrophils, monocytes, B-lymphocytes, CD-4+ T-lymphocytes, CD-8+ T-lymphocytes, and NK-cells generated from the blood of healthy donors (n = 3). Then, we examined the relationship between the whole-blood expression levels of the ten genes and white blood cell counts in a cohort of acute ischemic stroke patients (n = 36) and acute stroke mimics (n = 15) recruited at emergency department admission. All ten genes displayed strong patterns of lineage-specific expression in our analysis of isolated leukocytes, and their whole-blood expression levels were correlated with white blood cell differential across the total patient population, suggesting that many of them are likely differentially expressed in whole blood during stroke as an artifact of stroke-induced shifts in leukocyte counts. Specifically, factor analysis inferred that over 50% of the collective variance in their whole-blood expression levels across the patient population was driven by underlying variance in white blood cell counts alone. However, the cumulative expression levels of the ten genes displayed a superior ability to discriminate between stroke patients and stroke mimics relative to white blood cell differential, suggesting that additional less prominent factors influence their expression levels which add to their diagnostic utility. These findings not only provide insight regarding this particular panel of ten genes, but also into the results of prior stroke transcriptomics studies performed in whole blood.

Machine-learning approach identifies a pattern of gene expression in peripheral blood that can accurately detect ischaemic stroke.

Early and accurate diagnosis of stroke improves the probability of positive outcome. The objective of this study was to identify a pattern of gene expression in peripheral blood that could potentially be optimised to expedite the diagnosis of acute ischaemic stroke (AIS). A discovery cohort was recruited consisting of 39 AIS patients and 24 neurologically asymptomatic controls. Peripheral blood was sampled at emergency department admission, and genome-wide expression profiling was performed via microarray. A machine-learning technique known as genetic algorithm k-nearest neighbours (GA/kNN) was then used to identify a pattern of gene expression that could optimally discriminate between groups. This pattern of expression was then assessed via qRT-PCR in an independent validation cohort, where it was evaluated for its ability to discriminate between an additional 39 AIS patients and 30 neurologically asymptomatic controls, as well as 20 acute stroke mimics. GA/kNN identified 10 genes (ANTXR2, STK3, PDK4, CD163, MAL, GRAP, ID3, CTSZ, KIF1B and PLXDC2) whose coordinate pattern of expression was able to identify 98.4% of discovery cohort subjects correctly (97.4% sensitive, 100% specific). In the validation cohort, the expression levels of the same 10 genes were able to identify 95.6% of subjects correctly when comparing AIS patients to asymptomatic controls (92.3% sensitive, 100% specific), and 94.9% of subjects correctly when comparing AIS patients with stroke mimics (97.4% sensitive, 90.0% specific). The transcriptional pattern identified in this study shows strong diagnostic potential, and warrants further evaluation to determine its true clinical efficacy.

Predictors of Acute Stroke Mimics in 8187 Patients Referred to a Stroke Service

Some patients seen by a stroke team do not have cerebrovascular disease but a condition that mimics stroke. The purpose of this study was to determine the rate and predictors of stroke mimics in a large sample. This is an analysis of data from consecutive patients seen by the National Institutes of Health Stroke Program over 10years. Data were collected prospectively as a quality improvement initiative. Patients with a cerebrovascular event or a stroke mimic were compared with the Student t or Pearson chi-square test as appropriate, and logistic regression was done to identify independent predictors. The analysis included 8187 patients: 30% had a stroke mimic. Patients with a stroke mimic were younger, and the proportion of patients with a stroke mimic was higher among women, patients without any risk factors, those seen as a code stroke or who arrived to the emergency department via personal vehicle, and those who had the onset of symptoms while inpatients. The proportion of patients with a stroke mimic was marginally higher among African-Americans than Caucasians. Factors associated with the greatest odds of having a stroke mimic in the logistic regression were lack of a history of hypertension, atrial fibrillation or hyperlipidemia. One third of the patients seen by a stroke team over 10years had a stroke mimic. Factors associated with a stroke mimic may be ascertained by an emergency physician before calling the stroke team.