FABS

Development, assessment and validation of a novel nomogram model for predicting stroke mimics in stroke center：A single-center observational study

BACKGROUND

Early recognition and prediction of stroke mimics (SM) can avoid inappropriate recanalization therapy and delay in the management of SM etiology. The purpose of this study is to screen the predictors for SM and develop a novel predictive nomogram model for predicting SM. Meanwhile, the diagnostic performance of the nomogram model was evaluated and validated. The diagnostic efficacy of the nomogram model was also compared with four other SM structured scales.

METHODS

The clinical data of eligible patients were retrospectively enrolled as training datasets from January 2020 to December 2021; and the clinical data of eligible patients were prospectively enrolled as validation datasets from February to December 2022 in stroke center, Shengjing hospital, respectively. Univariate analysis and Lasso regression were used to select the optimal predictors for the training set, and a nomogram model was constructed by multivariate logistics regression, predictive scoring based on nomogram model is performed for each subject suffering from suspected acute ischemic stroke. Area under the curve (AUC), Hosmer-Lemeshow goodness-of-fit test, Calibration curve, decision curve analysis (DCA), clinical impact curve (CIC) analysis and bootstrap sampling were performed to assess and validate the predictive performance and clinical utility of the nomogram model, and the DeLong test was used to compare the overall diagnostic performance of the nomogram model with the other four structured SM scales. The Delong test was also conducted to assess the external reliability of the SM nomogram model by comparing the predictive diagnostic performance of the validation set with the training set. Additionally, the Calibration curve was utilized to evaluate the diagnostic calibration capability of the SM nomogram model in the validation set.

RESULTS

703 eligible patients (68 with SM, accounting for 9.7 %) were assigned to the training set, while 301 patients (26 with SM, accounting for 8.6 %) were assigned to the validation set. A nomogram model was then developed using these six parameters (SBP, history of epilepsy, isolated dizziness, isolated sensory impairment, headache, and absence of speech impairment symptoms), a dynamic web-based version of the nomogram was subsequently created. Comparing with four other scales, the nomogram model showed the highest overall diagnostic performance (AUC = 0.929, 95%CI = 0.908-0.947). The Hosmer-Lemeshow goodness-of-fit test was conducted to assess the agreement between the predicted SM values from the model and the observed SM values. The results of the test indicated a favorable consistency (χ2 = 9.299, P = 0.3177) between the predicted and observed SM. The results obtained from the analysis of the Calibration curve, DCA curve, and CIC analysis suggested that the nomogram possesses a favorable predictive capacity and superior clinical usefulness. Furthermore, the external validation demonstrated that there is no significant difference in the overall predictive diagnostic performance between the validation set and training set (0.929 vs 0.910, P > 0.05), thereby confirming the favorable stability of the nomogram model.

CONCLUSION

Our study firstly proposed a nomogram prediction approach based on the clinical features of SM, which could effectively predict the occurrence of SM. The utilization of the nomogram in stroke center proves advantageous for the identification and evaluation of SM, thereby enhancing diagnostic decision-making and strategies employed for suspected acute stroke patients.

Clinical characteristics and management of functional neurological disorders (FND) mimicking stroke in emergency settings: a functional stroke mimic cases

Background

FNDs mimicking a stroke represent a growing challenge in the emergency department (ED). A comprehensive diagnostic approach involving clinical evaluation and neuroimaging is essential to differentiate stroke from mimics. The safety profile of thrombolysis justifies its use where FNDs cannot be ruled out. This approach highlights the need for more precise diagnostic tools and protocols to improve patient care and reduce unnecessary treatments. Distinguishing FNDs from actual cerebrovascular events is critical yet difficult, particularly under time constraints. Given the urgency and potential severity of strokes, intravenous thrombolysis is frequently administered even when FNDs cannot be definitively excluded.

Methods

This retrospective study analyzed data of participants admitted to the Trieste University Hospital Stroke Unit between January 2018 and December 2022, focusing on those presenting with sudden-onset focal neurological deficits mimicking a stroke, with some presenting within the reperfusion treatment window (<4.5 h from symptoms onset). We obtained detailed clinical evaluations and neuroimaging, and administered thrombolytic therapy in selected cases.

Results and discussion

We included 84 participants presenting with stroke mimics (average age of 45 yo) predominantly female (65.5%). Most common presentations: hemiparesis or hemisensory loss (75%), speech disorder (10.7%), vertigo/gait disorders (4.8%). History of psychiatric disorders was found in 32.1% of cases, and 48.8% had prior neurological disease or stroke risk factors. Advanced neuroimaging was performed in 43 cases yielding normal or non-specific results. Thrombolysis was safely administered in 31%. Patients mostly recovered within the first 24 h from admission (44.7%). We compared this FND's sample with 291 patients with mild ischemic stroke (NIHSS ≤7).

Poor prediction of stroke mimics using validated stroke mimic scales in a large academic telestroke network

INTRODUCTION

Telestroke enables timely and remote evaluation of patients with acute stroke syndromes. However, stroke mimics represent more than 30% of this population. Given the resources required for the management of suspected acute ischemic stroke, several scales have been developed to help identify stroke mimics. Our objective was to externally validate four mimic scales (Khan Score (KS), TeleStroke Mimic Score (TS), simplified FABS (sFABS), and FABS) in a large, academic telestroke network.

METHODS

This is a retrospective, Institutional Review Board-exempt study of all patients who presented with suspected acute stroke syndromes and underwent video evaluation between 2019 and 2020 at a large academic telestroke network. Detailed chart review was conducted to extract both the variables needed to apply the mimic scales, the final diagnosis confirmed by final imaging, and discharge diagnosis (cerebral ischemic vs stroke mimic). Overall score performance was assessed by calculating the area under curve (AUC). Youden cutpoint was established for each scale and used to calculate sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and accuracy.

RESULTS

A total of 1043 patients were included in the final analysis. Final diagnosis of cerebral ischemia was made in 63.5% of all patients, and stroke mimic was diagnosed in 381 patients (36.5%). To predict stroke mimic, TS had the highest AUC (68.3), sensitivity (99.2%), and NPV (77.3%); KS had the highest accuracy (67.5%); FABS had the highest specificity (55.1%), and PPV (72.5%).

CONCLUSIONS

While each scale offers unique strengths, none was able to identify stroke mimics effectively enough to confidently apply in clinical practice. There remains a need for significant clinical judgment to determine the likelihood of stroke mimic at presentation.

Reviewing migraine-associated pathophysiology and its impact on elevated stroke risk

Migraine affects up to 20 percent of the global population and ranks as the second leading cause of disability worldwide. In parallel, ischemic stroke stands as the second leading cause of mortality and the third leading cause of disability worldwide. This review aims to elucidate the intricate relationship between migraine and stroke, highlighting the role of genetic, vascular, and hormonal factors. Epidemiological evidence shows a positive association between migraine, particularly with aura, and ischemic stroke (IS), though the link to hemorrhagic stroke (HS) remains inconclusive. The shared pathophysiology between migraine and stroke includes cortical spreading depression, endothelial dysfunction, and genetic predispositions, such as mutations linked to conditions like CADASIL and MELAS. Genetic studies indicate that common loci may predispose individuals to both migraine and stroke, while biomarkers such as endothelial microparticles and inflammatory cytokines offer insights into the underlying mechanisms. Additionally, hormonal influences, particularly fluctuations in estrogen levels, significantly impact migraine pathogenesis and stroke risk, highlighting the need for tailored interventions for women. The presence of a patent foramen ovale (PFO) in migraineurs further complicates their risk profile, with device closure showing promise in reducing stroke occurrence. Furthermore, white matter lesions (WMLs) are frequently observed in migraine patients, suggesting potential cognitive and stroke risks. This review hopes to summarize the links between migraine and its associated conditions and ischemic stroke, recognizing the profound implications for clinical management strategies for both disorders. Understanding the complex relationship between migraine and ischemic stroke holds the key to navigating treatment options and preventive interventions to enhance overall patient outcomes.

Clinical and Radiological Differences between Patients Diagnosed with Acute Ischemic Stroke and Chameleons at the Emergency Room: Insights from a Single-Center Observational Study

INTRODUCTION

Scarce data exist about clinical/radiological differences between acute ischemic strokes diagnosed in the emergency room (AISER) and stroke chameleons (SCs). We aimed at describing the differences observed in a comprehensive stroke center in Chile.

METHODS

Prospective observational study of patients with ischemic stroke syndromes admitted to the emergency room (ER) of Clínica Alemana between December 2014 and October 2023.

RESULTS

1,197 patients were included; of these 63 (5.2%, 95% CI: 4.1-6.6) were SC; these were younger (p < 0.001), less frequently hypertensive (p = 0.03), and they also had lower systolic (SBP) (p < 0.001), diastolic blood pressures (DBP) (p = 0.011), and NIHSS (p < 0.001). Clinically, they presented less frequently gaze (p = 0.008) and campimetry alterations (p = 0.03), facial (p < 0.001) and limb weakness (left arm [p = 0.004], right arm (p = 0.041), left leg (p = 0.001), right leg p = 0.0029), sensory abnormalities (p < 0.001), and dysarthria (p < 0.001). Neuroradiological evaluations included less frequently large vessel occlusions (p = 0.01) and other stroke locations (p = 0.005); they also differed in their etiologies (p < 0.001). Brainstem strokes (p < 0.001) and extinction/inattention symptoms (p < 0.001) were only seen in AISER. In multivariate analysis, younger age (OR: 0.945; 95% CI: 0.93-0.96), DBP (OR: 0.97; 95% CI, 0.95-0.99), facial weakness (OR: 0.39; 95% CI: 0.19-0.78), sensory abnormities (OR: 0.16.18; 95% CI, 0.05-0.4), infratentorial location (OR: 0.36; 95% CI, 0.15-0.78), posterior circulation involvement (OR: 3.02; 95% CI, 1.45-6.3), cardioembolic (OR: 3.5; 95% CI, 1.56-7.99), and undetermined (OR: 2.42; 95% CI, 1.22-4.7; 95%) etiologies, remained statistically significant. A stepwise analysis including only clinical elements present on the patient's arrival to the ER, demonstrates that age (OR: 0.95; 95% CI: 0.94-0.97), DBP (OR: 0.97; 95% CI, 0.95-0.99), the presence of atrial fibrillation (OR: 2.22; 95% CI, 1.04-4.75, NIHSS (OR: 0.88; 95% CI, 0.71-0.89) and the presence in NIHSS of 1a level of consciousness (OR: 5.66; CI: 95% 1.8-16.9), 1b level of consciousness questions (OR: 3.023; 95% CI, 1.35-6.8), facial weakness (OR: 0.3; CI: 95% 0.17-0.8), and sensory abnormalities (OR: 0.27; 95% CI, 0.1-0.72) remained statistically significant.

CONCLUSION

SC had clinical and radiological differences compared to AISER. An additional relevant finding is that neurological symptoms in a patient with atrial fibrillation, even with a negative diffusion-weighted imaging, should be carefully evaluated as a potential stroke until other causes are satisfactorily ruled out.

The Burden of Stroke Mimics Among Hyperacute Stroke Unit Attendees with Special Emphasis on Migraine: A 10-Year Evaluation

BACKGROUND AND OBJECTIVES

Stroke and migraine are common neurological illnesses that cause tremendous suffering for patients. Certain diseases can mimic the clinical manifestations of an actual stroke. Migraine is one of the most commonly reported stroke mimics. The main goals of this study are to look at the prevalence of stroke mimics on the stroke pathway of Sheffield Teaching Hospitals and how many of them are migraines.

MATERIALS AND METHODS

A retrospective service evaluation was conducted at the hyperacute stroke unit (HASU) of the Royal Hallamshire Hospital (RHH) in the United Kingdom. The total admissions from 2013 to 2022 were collected from the Sentinel Stroke National Audit Programme database, and the number of stroke mimics was evaluated each year. The burden of migraine stroke mimics was also evaluated. Then, a one-year sample of stroke mimics was extracted to look for the types of each mimic.

RESULTS

From 2013 to 2022, 45.75% (n = 12156) of the stroke pathway patients (n = 26573) were stroke mimics, with an increment of up to 55% in the years 2021 and 2022. During these 10 years, migraine stroke mimics accounted for 10.21% of admissions (n = 1240). The three most common mimics in a one-year sample of stroke pathway patients were migraine (14.70%) (n = 373), functional neurological disorders (FNDs) (7.17%) (n = 182), and Guillain-Barré syndrome (6.66%) (n = 169). Seizures, syncope, and metabolic derangements were reported as mimics in 4.17% (n = 106), 3.14% (n = 80), and 1.77% (n = 45), respectively.

CONCLUSIONS

About half of the HASU attendees were stroke mimics rather than actual strokes, and the most common mimics were migraines.

Mollet I, Mendonça M, Salavisa M, Meira B, Fernandes M, Serrazina F, Cabral G, Ventura R, Sobral‐Pinho A, Beck HC, Vieira HLA, Viana‐Baptista M, Matthiesen R. Proteomics to Identify New Blood Biomarkers for Diagnosing Patients With Acute Stroke

BACKGROUND

Blood biomarkers are a potential tool for early stroke diagnosis. We aimed to perform a pilot and exploratory study on untargeted blood biomarkers in patients with suspected stroke by using mass spectrometry analysis.

METHODS AND RESULTS

This was a prospective observational study of consecutive patients with suspected stroke admitted within 6 hours of last being seen well. Blood samples were collected at admission. Patients were divided into 3 groups: ischemic stroke (IS), intracerebral hemorrhage (ICH), and stroke mimics. Quantitative analysis from mass spectrometry data was performed using a supervised approach. Biomarker-based prediction models were developed to differentiate IS from ICH and ICH+stroke mimics. Models were built aiming to minimize misidentification of patients with ICH as having IS. We included 90 patients, one-third within each subgroup. The median age was 71 years (interquartile range, 57-81 years), and 49 participants (54.4%) were women. In quantitative analysis, C3 (complement component 3), ICAM-2 (intercellular adhesion molecule 2), PLGLA (plasminogen like A), STXBP5 (syntaxin-binding protein 5), and IGHV3-64 (immunoglobulin heavy variable 3-64) were the 5 most significantly dysregulated proteins for both comparisons. Biomarker-based models showed 88% sensitivity and 89% negative predictive value for differentiating IS from ICH, and 75% sensitivity and 95% negative predictive value for differentiating IS from ICH+stroke mimics. ICAM-2, STXBP5, PLGLA, C3, and IGHV3-64 displayed the highest importance score in our models, being the most informative for identifying patients with stroke.

CONCLUSIONS

In this proof-of-concept and exploratory study, our biomarker-based prediction models, including ICAM-2, STXBP5, PLGLA, C3, and IGHV3-64, showed 75% to 88% sensitivity for identifying patients with IS, while aiming to minimize misclassification of ICH. Although our methodology provided an internal validation, these results still need validation in other cohorts and with different measurement techniques.

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.

Validating Existing Scales for Identification of Acute Stroke in an Inpatient Setting

Background and Purpose

A significant proportion of strokes occur while patients are hospitalized for other reasons. Numerous stroke scales have been developed and validated for use in pre-hospital and emergency department settings, and there is growing interest to adapt these scales for use in the inpatient setting. We aimed to validate existing stroke scales for inpatient stroke codes.

Methods

We retrospectively reviewed charts from inpatient stroke code activations at an urban academic medical center from January 2016 through December 2018. Receiver operating characteristic analysis was performed for each specified stroke scale including NIHSS, FAST, BE-FAST, 2CAN, FABS, TeleStroke Mimic, and LAMS. We also used logistic regression to identify independent predictors of stroke and to derive a novel scale.

Results

Of the 958 stroke code activations reviewed, 151 (15.8%) had a final diagnosis of ischemic or hemorrhagic stroke. The area under the curve (AUC) of existing scales varied from .465 (FABS score) to .563 (2CAN score). Four risk factors independently predicted stroke: (1) recent cardiovascular procedure, (2) platelet count less than 50 × 109 per liter, (3) gaze deviation, and (4) presence of unilateral leg weakness. Combining these 4 factors into a new score yielded an AUC of .653 (95% confidence interval [CI] .604-.702).

Conclusion

This study suggests that currently available stroke scales may not be sufficient to differentiate strokes from mimics in the inpatient setting. Our data suggest that novel approaches may be required to help with diagnosis in this unique population.

A Machine Learning Approach to Support Urgent Stroke Triage Using Administrative Data and Social Determinants of Health at Hospital Presentation: Retrospective Study

BACKGROUND

The key to effective stroke management is timely diagnosis and triage. Machine learning (ML) methods developed to assist in detecting stroke have focused on interpreting detailed clinical data such as clinical notes and diagnostic imaging results. However, such information may not be readily available when patients are initially triaged, particularly in rural and underserved communities.

OBJECTIVE

This study aimed to develop an ML stroke prediction algorithm based on data widely available at the time of patients' hospital presentations and assess the added value of social determinants of health (SDoH) in stroke prediction.

METHODS

We conducted a retrospective study of the emergency department and hospitalization records from 2012 to 2014 from all the acute care hospitals in the state of Florida, merged with the SDoH data from the American Community Survey. A case-control design was adopted to construct stroke and stroke mimic cohorts. We compared the algorithm performance and feature importance measures of the ML models (ie, gradient boosting machine and random forest) with those of the logistic regression model based on 3 sets of predictors. To provide insights into the prediction and ultimately assist care providers in decision-making, we used TreeSHAP for tree-based ML models to explain the stroke prediction.

RESULTS

Our analysis included 143,203 hospital visits of unique patients, and it was confirmed based on the principal diagnosis at discharge that 73% (n=104,662) of these patients had a stroke. The approach proposed in this study has high sensitivity and is particularly effective at reducing the misdiagnosis of dangerous stroke chameleons (false-negative rate <4%). ML classifiers consistently outperformed the benchmark logistic regression in all 3 input combinations. We found significant consistency across the models in the features that explain their performance. The most important features are age, the number of chronic conditions on admission, and primary payer (eg, Medicare or private insurance). Although both the individual- and community-level SDoH features helped improve the predictive performance of the models, the inclusion of the individual-level SDoH features led to a much larger improvement (area under the receiver operating characteristic curve increased from 0.694 to 0.823) than the inclusion of the community-level SDoH features (area under the receiver operating characteristic curve increased from 0.823 to 0.829).

CONCLUSIONS

Using data widely available at the time of patients' hospital presentations, we developed a stroke prediction model with high sensitivity and reasonable specificity. The prediction algorithm uses variables that are routinely collected by providers and payers and might be useful in underresourced hospitals with limited availability of sensitive diagnostic tools or incomplete data-gathering capabilities.

Stroke Scales as Assessment Tools in Emergency Settings: A Narrative Review

In the last 20 years, substantial improvements have been made in stroke recanalization treatment. Good outcomes after modern reperfusion treatment require the rapid and accurate identification of stroke patients. Several stroke rating scales are available or have been proposed for the early recognition of stroke and the evaluation of stroke severity and outcome. This review aims to provide an overview of commonly used stroke scales in emergency and clinical settings. The most commonly used scale in a prehospital setting for stroke recognition is the Face, Arms, Speech, Time (FAST) test. Among many prehospital stroke scales, the Los Angeles Prehospital Stroke Screen has the highest sensitivity and specificity for confirming stroke diagnosis. The National Institutes of Health Stroke Scale (NIHSS) is the most recommended tool for the evaluation of stroke patients in hospital settings and research, and it has two variants: the shortened NIHSS for Emergency Medical Service and the modified NIHSS. The evaluation of comatose patients usually involves assessment with the Glasgow Coma Scale, which is very useful in patients with hemorrhagic stroke or traumatic brain injury. In patients with subarachnoid hemorrhage, the outcome is usually accessed with the Hunt and Hess scale. A commonly used tool for stroke outcome evaluation in clinical/hospital settings and research is the modified Rankin scale. The tools for disability evaluation are the Barthel Index and Functional Independence Measure.

Multilayer perceptron-based prediction of stroke mimics in prehospital triage

The identification of stroke mimics (SMs) in patients with stroke could lead to delayed diagnosis and waste of medical resources. Multilayer perceptron (MLP) was proved to be an accurate tool for clinical applications. However, MLP haven't been applied in patients with suspected stroke onset within 24 h. Here, we aimed to develop a MLP model to predict SM in patients. We retrospectively reviewed the data of patients with a prehospital diagnosis of suspected stroke between July 2017 and June 2021. SMs were confirmed during hospitalization. We included demographic information, clinical manifestations, medical history, and systolic and diastolic pressure on admission. First, the cohort was randomly divided into a training set (70%) and an external testing set (30%). Then, the least absolute shrinkage and selection operator (LASSO) method was used in feature selection and an MLP model was trained based on the selected items. Then, we evaluated the performance of the model using the ten-fold cross validation method. Finally, we used the external testing set to compare the MLP model with FABS scoring system (FABS) and TeleStroke Mimic Score (TM-Score) using a receiver operator characteristic (ROC) curve. In total, 402 patients were included. Of these, 82 (20.5%) were classified as SMs. During the ten-fold cross validation, the mean area under the ROC curve (AUC) of 10 training sets and 10 validation sets were 0.92 and 0.87, respectively. In the external testing set, the AUC of the MLP model was significantly higher than that of the FABS (0.855 vs. 0.715, P = 0.038) and TM-Score (0.855 vs. 0.646, P = 0.006). The MLP model had significantly better performance in predicting SMs than FABS and TM-Score.

Clinical Differences Between Stroke and Stroke Mimics in Code Stroke Patients

BACKGROUND

The 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).

METHODS

We 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.

RESULTS

A 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).

CONCLUSION

Some 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.

Pharmacological brain cytoprotection in acute ischaemic stroke — renewed hope in the reperfusion era

For over 40 years, attempts to develop treatments that protect neurons and other brain cells against the cellular and biochemical consequences of cerebral ischaemia in acute ischaemic stroke (AIS) have been unsuccessful. However, the advent of intravenous thrombolysis and endovascular thrombectomy has taken us into a new era of treatment for AIS in which highly effective reperfusion therapy is widely available. In this context, cytoprotective treatments should be revisited as adjunctive treatment to reperfusion therapy. Renewed efforts should focus on developing new drugs that target multiple aspects of the ischaemic cascade, and previously developed drugs should be reconsidered if they produced robust cytoprotective effects in preclinical models and their safety profiles were reasonable in previous clinical trials. Several development pathways for cytoprotection as an adjunct to reperfusion can be envisioned. In this Review, we outline the targets for cytoprotective therapy and discuss considerations for future drug development, highlighting the recent ESCAPE-NA1 trial of nerinetide, which produced the most promising results to date. We review new types of clinical trial to evaluate whether cytoprotective drugs can slow infarct growth prior to reperfusion and/or ameliorate the consequences of reperfusion, such as haemorrhagic transformation. We also highlight how advanced brain imaging can help to identify patients with salvageable ischaemic tissue who are likely to benefit from cytoprotective therapy.

In this Review, Fisher and Savitz consider how the era of reperfusion therapy in ischaemic stroke provides new hope for the development of cytoprotective therapies to further improve outcomes, highlighting how promising recent findings can be built on to benefit patients.

Highly successful reperfusion therapy with intravenous thrombolysis and endovascular thrombectomy is now widely available for the treatment of acute ischaemic stroke, making cytoprotective therapy a viable additional treatment approach.

Previous attempts to develop cytoprotective therapy have been unsuccessful, but this approach should now be reconsidered as an adjunctive therapy to thrombolysis and thrombectomy.

New cytoprotective drugs should be developed to target multiple aspects of the ischaemic cascade, and previously developed drugs should be reconsidered.

Trials should be conducted to evaluate the effects of cytoprotective drugs when administered before or after reperfusion therapy or both.

Advanced brain imaging should be used to select patients who are most likely to benefit from cytoprotective treatment for enrolment in new trials.

Stroke Mimics on the Stroke Unit - Temporal trends 2008-2017 at a large Norwegian university hospital

OBJECTIVES

The objective was to quantify temporal trends in stroke mimics (SM) admissions relative to cerebrovascular accidents (CVA), incidence of hospitalized SMs and characterize the SM case-mix at a general hospital's stroke unit (SU).

MATERIALS & METHODS

All SU admissions (n = 11240) of patients aged 15 or older to Haukeland University Hospital between 2008-2017 were prospectively included and categorized as CVA or SM. Logistic regression was used to estimate time trends in the proportion of SMs among the admissions. Poisson regression was used to estimate time trends in age- and sex-dependent SM incidence.

RESULTS

SMs were on average younger thaan CVA patients (68.3 vs. 71.4 years) and had a higher proportion of females (53.6% vs. 44.5%). The total proportion of SM admissions was 51.0%. There was an increasing time trend in the proportion of SM admissions, odds ratio 1.150 per year (p < 0.001), but this trend appears flattening, represented by a significant quadratic time-term, odds ratio 1.009 (p < 0.001). A higher SM proportion was also associated with the time period of a Mass Media Intervention (FAST campaign) in 2014. There was also an increasing trend in SM incidence, that remains after adjusting for age, sex, and population; also, for incidence the trend appears to be flattening.

CONCLUSIONS

SMs account for approximately half of the SU admissions, and the proportion has been increasing. A FAST campaign appears to have temporarily increased the SM proportion. The age- and sex-dependent incidence of SM has been increasing but appears to flatten out.

Ultra-Early Differential Diagnosis of Acute Cerebral Ischemia and Hemorrhagic Stroke by Measuring the Prehospital Release Rate of GFAP

BACKGROUND

Plasma glial fibrillary acidic protein (GFAP) and tau are promising markers for differentiating acute cerebral ischemia (ACI) and hemorrhagic stroke (HS), but their prehospital dynamics and usefulness are unknown.

METHODS

We performed ultra-sensitivite single-molecule array (Simoa®) measurements of plasma GFAP and total tau in a stroke code patient cohort with cardinal stroke symptoms [National Institutes of Health Stroke Scale (NIHSS) ≥3]. Sequential sampling included 2 ultra-early samples, and a follow-up sample on the next morning.

RESULTS

We included 272 cases (203 ACI, 60 HS, and 9 stroke mimics). Median (IQR) last-known-well to sampling time was 53 (35-90) minutes for initial prehospital samples, 90 (67-130) minutes for secondary acute samples, and 21 (16-24) hours for next morning samples. Plasma GFAP was significantly higher in patients with HS than ACI (P < 0.001 for <1 hour and <3 hour prehospital samples, and <3 hour secondary samples), while total tau showed no intergroup difference. The prehospital GFAP release rate (pg/mL/minute) occurring between the 2 very early samples was significantly higher in patients with HS than ACI [2.4 (0.6-14.1)] versus 0.3 (-0.3-0.9) pg/mL/minute, P < 0.001. For cases with <3 hour prehospital sampling (ACI n = 178, HS n = 59), a combined rule (prehospital GFAP >410 pg/mL, or prehospital GFAP 90-410 pg/mL together with GFAP release >0.6 pg/mL/minute) enabled ruling out HS with high certainty (NPV 98.4%) in 68% of patients with ACI (sensitivity for HS 96.6%, specificity 68%, PPV 50%).

CONCLUSIONS

In comparison to single-point measurement, monitoring the prehospital GFAP release rate improves ultra-early differentiation of stroke subtypes. With serial measurement GFAP has potential to improve future prehospital stroke diagnostics .

Telestroke consultation can accurately diagnose ischemic stroke mimics

INTRODUCTION

Telestroke (TS) networks are standard in many areas of the US. Despite TS systems having approximately 33% mimic rates, it is unknown if TS can accurately diagnose patients with acute ischemic stroke (AIS) versus stroke mimics.

METHODS

We performed a retrospective review of consecutive TS consults to 27 TS sites in six states during 2018. Clinical information and diagnosis were extracted from discharge records and compared to those from the TS consult. Discharge diagnoses were verified and coded into 12 categories. Cases without a clear discharge diagnosis and intracerebral haemorrhage were excluded. We report agreement and a Cohen's kappa between TS and discharge diagnoses for the category of AIS/transient ischemic attack (TIA) versus stroke mimic.

RESULTS

We included 404 cases in the analysis (mean age 66 years; 54% women). Of these, 225 had a TS diagnosis of AIS/TIA; 102 (45%) received intravenous tissue plasminogen activator. Our study demonstrated a high diagnostic agreement for AIS/TIA (88%) with a kappa of 0.75 for stroke and mimics. Of the 179 patients diagnosed with a stroke mimic on TS, 27 (15%) were diagnosed with AIS/TA by discharge. TS mimic diagnosis had a positive predictive value (PPV) of 85% and a negative predictive value (NPV) of 90%; TS diagnosis of stroke/TIA had PPV 90%, NPV 85%.

DISCUSSION

We found excellent correlation between TS and discharge diagnoses for patients with both stroke and stroke mimics. This suggests that TS systems can accurately assess a wider variety of patients with acute neurologic syndromes other than AIS.

External validation of stroke mimic prediction scales in the emergency department

BACKGROUND

Acute ischemic stroke is a time-sensitive emergency where accurate diagnosis is required promptly. Due to time pressures, stroke mimics who present with similar signs and symptoms as acute ischemic stroke, pose a diagnostic challenge to the emergency physician. With limited access to investigative tools, clinical prediction, tools based only on clinical features, may be useful to identify stroke mimics. We aim to externally validate the performance of 4 stroke mimic prediction scales, and derive a novel decision tree, to improve identification of stroke mimics.

METHODS

We performed a retrospective cross-sectional study at a primary stroke centre, served by a telestroke hub. We included consecutive patients who were administered intravenous thrombolysis for suspected acute ischemic stroke from January 2015 to October 2017. Four stroke mimic prediction tools (FABS, simplified FABS, Telestroke Mimic Score and Khan Score) were rated simultaneously, using only clinical information prior to administration of thrombolysis. The final diagnosis was ascertained by an independent stroke neurologist. Area under receiver operating curve (AUROC) analysis was performed. A classification tree analysis was also conducted using variables which were found to be significant in the univariate analysis.

RESULTS

Telestroke Mimic Score had the highest discrimination for stroke mimics among the 4 scores tested (AUROC = 0.75, 95% CI = 0.63-0.87). However, all 4 scores performed similarly (DeLong p > 0.05). Telestroke Mimic Score had the highest sensitivity (91.3%), while Khan score had the highest specificity (88.2%). All 4 scores had high positive predictive value (88.1 to 97.5%) and low negative predictive values (4.7 to 32.3%). A novel decision tree, using only age, presence of migraine and psychiatric history, had a higher prediction performance (AUROC = 0.80).

CONCLUSION

Four tested stroke mimic prediction scales performed similarly to identify stroke mimics in the emergency setting. A novel decision tree may improve the identification of stroke mimics.

Stroke mimics in patients clinically diagnosed with stroke at a tertiary teaching hospital in Tanzania: a prospective cohort study

BACKGROUND

Stroke mimics account for up to one-third of acute stroke admissions and are a heterogeneous entity which pose diagnostic challenges. Diagnosing such patients is however crucial to avoid delays in treatment and potentially harmful medication prescription. We aimed at describing the magnitude, clinical characteristics and short-term outcomes of stroke mimics in patients clinically diagnosed with a stroke.

METHODS

This prospective study enrolled patients admitted with a World Health Organization clinical criteria for stroke at a tertiary hospital in Tanzania. Baseline data was collected and the simplified version of the FABS scale was used to determine its usefulness in predicting stroke mimics. The National Institute of Health Stroke Scale and Modified Rankin Scale were used to assess for admission stroke severity and outcomes respectively.

RESULTS

Among 363 patients with suspected stroke on admission, the final diagnosis was stroke mimics in 24 (6.6%) who had a mean age of 65.8 ± 15 years. Patients with stroke mimics were less likely to have cardiovascular risk factors for stroke including premorbid hypertension (7 (29.2%) vs 263 (77.6%), p < 0.001) and increased waist-hip ratio (9 (37.5%) vs 270 (79.6%) p < 0.001) for mimics and true strokes respectively. Clinical findings such as hypertension and the presence of cortical features in neurological examination occurred less in patients with stroke mimics. The simplified FABS score of ≥3 could identify patients with stroke mimics with a sensitivity and specificity of 38 and 80% respectively. The most common causes of mimics were brain tumors 6 (25%), meningoencephalitis 4 (16.7%) and epileptic seizures 3 (12.5%). The majority of patients with stroke mimics had severe disease on admission and the 30-day mortality in these patients was 54.5%.

CONCLUSIONS

In the present study, the proportion of stroke mimics among patients clinically diagnosed with stroke was 6.6% and brain tumors was a common etiology. Stroke mimics were less likely to have cardiovascular risk factors and cortical signs during evaluation. We recommend further studies that can help develop clinical scales used for predicting stroke mimics in an African population.

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

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Positive predictive value of stroke identification by ambulance clinicians in North East England: a service evaluation

INTRODUCTION/BACKGROUND

Accurate prehospital identification of patients who had an acute stroke enables rapid conveyance to specialist units for time-dependent treatments such as thrombolysis and thrombectomy. Misidentification leads to patients who had a 'stroke mimic' (SM) being inappropriately triaged to specialist units. We evaluated the positive predictive value (PPV) of prehospital stroke identification by ambulance clinicians in the North East of England.

METHODS

This service evaluation linked routinely collected records from a UK regional ambulance service identifying adults with any clinical impression of suspected stroke to diagnostic data from four National Health Service hospital trusts between 1 June 2013 and 31 May 2016. The reference standard for a confirmed stroke diagnosis was inclusion in Sentinel Stroke National Audit Programme data or a hospital diagnosis of stroke or transient ischaemic attack in Hospital Episode Statistics. PPV was calculated as a measure of diagnostic accuracy.

RESULTS

Ambulance clinicians in North East England identified 5645 patients who had a suspected stroke (mean age 73.2 years, 48% male). At least one Face Arm Speech Test (FAST) symptom was documented for 93% of patients who had a suspected stroke but a positive FAST was only documented for 51%. Stroke, or transient ischaemic attack, was the final diagnosis for 3483 (62%) patients. SM (false positives) accounted for 38% of suspected strokes identified by ambulance clinicians and included a wide range of non-stroke diagnoses including infections, seizures and migraine.

DISCUSSION

In this large multisite data set, identification of patients who had a stroke by ambulance clinicians had a PPV rate of 62% (95% CI 61 to 63). Most patients who had a suspected stroke had at least one FAST symptom, but failure to document a complete test was common. Training for stroke identification and SM rates need to be considered when planning service provision and capacity.

Experimental study on differential diagnosis of cerebral hemorrhagic and ischemic stroke based on microwave measurement

BACKGROUND

Hemorrhagic stroke and ischemic stroke have similar symptoms at the onset of the disease, but their clinical treatment is completely different. The early, effective identification of stroke types can effectively improve the cure rate.

OBJECTIVE

In this study, an early, noncontact identification of the stroke type, i.e., hemorrhagic or ischemic, based on a microwave measurement technique was investigated.

METHODS

This study was based on animal models of cerebral hemorrhage and cerebral ischemia and the design of a microwave scattering parameter measurement system.

RESULTS

The accuracy of the cerebral hemorrhage model with a blood loss interval of 2 ml reached 93.75%. While the accuracy of the cerebral ischemia model with an ischemic interval of 42 minutes reached 91.7%.

CONCLUSION

The experimental results show that the system for identifying cerebral stroke based on microwaves can distinguish between cerebral hemorrhage and cerebral ischemia models and effectively distinguish between different degrees of cerebral hemorrhage or different durations of cerebral ischemia. This experimental system is inexpensive, portable, noninvasive, simple, and rapid and thus has good potential as a method for identifying the stroke type prior to hospitalization.

Diagnostic accuracy of clinical tools for assessment of acute stroke: a systematic review

INTRODUCTION

Recanalisation therapy in acute ischaemic stroke is highly time-sensitive, and requires early identification of eligible patients to ensure better outcomes. Thus, a number of clinical assessment tools have been developed and this review examines their diagnostic capabilities.

METHODS

Diagnostic performance of currently available clinical tools for identification of acute ischaemic and haemorrhagic strokes and stroke mimicking conditions was reviewed. A systematic search of the literature published in 2015-2018 was conducted using PubMed, EMBASE, Scopus and The Cochrane Library. Prehospital and in-hospital studies with a minimum sample size of 300 patients reporting diagnostic accuracy were selected.

RESULTS

Twenty-five articles were included. Cortical signs (gaze deviation, aphasia and neglect) were shown to be significant indicators of large vessel occlusion (LVO). Sensitivity values for selecting subjects with LVO ranged from 23 to 99% whereas specificity was 24 to 97%. Clinical tools, such as FAST-ED, NIHSS, and RACE incorporating cortical signs as well as motor dysfunction demonstrated the best diagnostic accuracy. Tools for identification of stroke mimics showed sensitivity varying from 44 to 91%, and specificity of 27 to 98% with the best diagnostic performance demonstrated by FABS (90% sensitivity, 91% specificity). Hypertension and younger age predicted intracerebral haemorrhage whereas history of atrial fibrillation and diabetes were associated with ischaemia. There was a variation in approach used to establish the definitive diagnosis. Blinding of the index test assessment was not specified in about 50% of included studies.

CONCLUSIONS

A wide range of clinical assessment tools for selecting subjects with acute stroke has been developed in recent years. Assessment of both cortical and motor function using RACE, FAST-ED and NIHSS showed the best diagnostic accuracy values for selecting subjects with LVO. There were limited data on clinical tools that can be used to differentiate between acute ischaemia and haemorrhage. Diagnostic accuracy appeared to be modest for distinguishing between acute stroke and stroke mimics with optimal diagnostic performance demonstrated by the FABS tool. Further prehospital research is required to improve the diagnostic utility of clinical assessments with possible application of a two-step clinical assessment or involvement of simple brain imaging, such as transcranial ultrasonography.

Migraine History: A Predictor of Negative Diffusion-Weighted Imaging in IV-tPA-Treated Stroke Mimics

BACKGROUND

Migraine, seizures, and psychiatric disorders are frequently reported as "stroke mimics" in patients with negative diffusion-weighted imaging (DWI) after IV-tPA. We sought to determine predictors of negative DWI in suspected stroke patients treated with IV-tPA.

METHOD

A retrospective case-control study encompassing all acute stroke patients treated with IV-tPA (at our hospital or "dripped and shipped") from January 2013 to December 2014 was con- ducted. A total of 275 patients were identified with 47 negative DWI cases and 228 positive DWI controls. Variables including demographic factors, stroke characteristics, and clinical comorbidities were analyzed for statistical significance. A multivariate logistic regression was performed (SPSS-24) to identify predictors of negative DWI.

RESULTS

Approximately 17% of patients had negative DWI after IV-tPA. Compared to controls, migraine history independently predicted negative DWI (odds ratio [OR] 5.0 95% confidence interval [CI] 1.03-24.6, P = .046). Increasing age (OR .97 95% CI .94-.99, P = .02) and atrial fibrillation (OR .25 95% CI .08-.77, P = .01) predicted lower probability of negative DWI. Gender, admission NIHSS, treatment location, preadmission modified Rankin scale, diabetes mellitus, hypertension, hyperlipidemia, symptom side, seizure history, and psychiatric history did not predict negative DWI status.

CONCLUSIONS

In our study, roughly 1 in 6 patients treated with IV-tPA were later found to be stroke mimics with negative DWI. Despite a high proportion of suspected stroke mimics in our study, only preexisting migraine history independently predicted negative DWI status after IV-tPA treatment in suspected stroke patients.

Migraine as a Stroke Mimic and as a Stroke Chameleon

PURPOSE OF REVIEW

This review details the frequency of and ways in which migraine can be both an ischemic stroke/transient ischemic attack mimic (false positive) and chameleon (false negative). We additionally seek to clarify the complex relationships between migraine and cerebrovascular diseases with regard to diagnostic error.

RECENT FINDINGS

Nearly 2% of all patients evaluated emergently for possible stroke have an ultimate diagnosis of migraine; approximately 18% of all stroke mimic patients treated with intravenous thrombolysis have a final diagnosis of migraine. Though the treatment of a patient with migraine with thrombolytics confers a low risk of complication, symptomatic intracerebral hemorrhage may occur. Three clinical prediction scores with high sensitivity and specificity exist that can aid in the diagnosis of acute cerebral ischemia. Differentiating between migraine aura and transient ischemic attacks remains challenging. On the other hand, migraine is a common incorrect diagnosis initially given to patients with stroke. Among patients discharged from an emergency visit to home with a diagnosis of a non-specific headache disorder, 0.5% were misdiagnosed. Further development of tools to quantify and understand sources of stroke misdiagnosis among patients who present with headache is warranted. Both failure to identify cerebral ischemia among patients with headache and overdiagnosis of ischemia can lead to patient harms. While some tools exist to help with acute diagnostic decision-making, additional strategies to improve diagnostic safety among patients with migraine and/or cerebral ischemia are needed.

Hemicraniectomy for Malignant Middle Cerebral Artery Syndrome: A Review of Functional Outcomes in Two High-Volume Stroke Centers

BACKGROUND AND PURPOSE

Despite recent landmark randomized controlled trials showing significant benefits for hemicraniectomy (HCT) compared with medical therapy (MT) in patients with malignant middle cerebral artery infarction (MMCAI), HCT rates have not substantially increased in the United States. We sought to evaluate early outcomes in patients with MMCAI who were treated with HCT (cases) in comparison to patients treated with MT due to the perception of procedural futility by families (controls).

METHODS

We retrospectively evaluated consecutive patients with acute MMCAI treated in 2 tertiary care centers during a 7-year period. Pretreatment National Institutes of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS) at 3 months were documented. Functional independence (FI) and survival without severe disability (SWSD) were defined as mRS of 0-2 and 0-4, respectively.

RESULTS

A total of 66 patients (37 cases and 29 controls) fulfilled the study inclusion criteria (mean age 59 ± 15 years, 52% men, median admission NIHSS score: 19 points [interquartile range {IQR}: 16-22]). Cases were younger (51 ± 11 versus 68 ± 13 years; P < .001) and tended to have lower median admission NIHSS than controls (18 [IQR:16-20] versus 20 [IQR:18-23]; P = .072). The rates of FI and SWSD at 3 months were higher in cases than controls (16% versus 0% [P = .031] and 62% versus 0% [P < .001]), while 3-month mortality was lower (24% versus 77%; P < .001). Multivariable Cox regression analyses adjusting for potential confounders identified HCT as the most important predictor of lower risk of 3-month mortality (hazard ratio: .02, 95% confidence interval: .01-0.10; P < .001).

CONCLUSIONS

HCT is a critical and effective therapy for patients with MMCAI but cannot provide a guarantee of functional recovery.

Inter-rater Agreement for the Diagnosis of Stroke Versus Stroke Mimic

BACKGROUND AND PURPOSE

Patients who present emergently with acute neurological signs and symptoms represent unique diagnostic challenges for clinicians. We sought to characterize the reliability of physician diagnosis in differentiating aborted or imaging-negative acute ischemic stroke from stroke mimic.

METHODS

We constructed 10 case-vignettes of patients treated with thrombolysis with subsequent clinical improvement who lacked radiographic evidence of infarction. Using an online survey, we asked physicians to select a most likely final diagnosis after reading each case-vignette. Inter-rater agreement was evaluated using percent agreement and κ statistic for multiple raters with 95% confidence intervals reported.

RESULTS

Sixty-five physicians participated in the survey. Most participants were in practice for ≥5 years and over half were vascular neurologists. Physicians agreed on the most likely final diagnosis 71% of the time, κ of 0.21 (95% confidence interval, 0.06-0.54). Percent agreement was similar across participant practice locations, years of experience, subspecialty training, and personal experience with thrombolysis.

CONCLUSIONS

We found modest agreement among surveyed physicians in distinguishing ischemic stroke syndromes from stroke mimics in patients without radiographic evidence of infarction and clinical improvement after thrombolysis. Methods to improve diagnostic consensus after thrombolysis are needed to assure acute ischemic stroke patients and stroke mimics are treated safely and accurately.

Safety and predictors of stroke mimics in The Norwegian Tenecteplase Stroke Trial (NOR-TEST)

Background

Stroke mimics are frequently treated with thrombolysis in clinical practice and thrombolytic trials. Although alteplase in stroke mimics has proven to be safe, safety of tenecteplase in stroke mimics has not been assessed in an ischemic stroke study setting. We aimed to assess clinical characteristics and safety of stroke mimics treated with thrombolysis in the Norwegian Tenecteplase Stroke Trial. We also aimed to identify possible predictors of stroke mimics as compared to patients with acute cerebral ischemia.

Methods

Norwegian Tenecteplase Stroke Trial was a phase-3 trial investigating safety and efficacy of tenecteplase vs. alteplase in patients with suspected acute cerebral ischemia. Two groups were defined based on diagnose at discharge: patients with a different diagnose than ischemic stroke or transient ischemic attack (stroke mimics group) and patients diagnosed with ischemic stroke or transient ischemic attack (acute cerebral ischemia group). Logistic regression analyses were performed with stroke mimics vs. acute cerebral ischemia as dependent variable to identify predictors of stroke mimics.

Results

Of 1091 randomized patients, 181 (16.6%) were stroke mimics. Migraine (22.2%) and peripheral vertigo (11.4%) were the two most frequent stroke mimic-diagnoses. There was no symptomatic intracerebral hemorrhage in the stroke mimics group. Stroke mimics were independently associated with age ≤60 years (OR 2.75, p < 0.001), female sex (OR 1.48, p = 0.026), no history of myocardial infarction (OR 2.03, p = 0.045), systolic BP ≤ 150 mmHg (OR 2.33, p < 0.001), NIHSS ≤ 6 points (OR 1.83, p = 0.011), sensory loss (OR 1.55, p = 0.015), and no facial paresis (OR 2.41, p < 0.001) on admission.

Conclusion

Thrombolysis with tenecteplase seems to be as safe as with alteplase in stroke mimics. Predictors were identified for stroke mimics which may contribute to differentiate stroke mimics from acute cerebral ischemia in future stroke trials.

Diagnosing cerebral ischemia with door-to-thrombolysis times below 20 minutes

Objectives

To clarify diagnostic accuracy and consequences of misdiagnosis in the admission evaluation of stroke-code patients in a neurologic emergency department with less than 20-minute door-to-thrombolysis times.

Methods

Accuracy of admission diagnostics was studied in an observational cohort of 1,015 stroke-code patients arriving by ambulance as candidates for recanalization therapy between May 2013 and November 2015. Immediate admission evaluation was performed by a stroke neurologist or a neurology resident with dedicated stroke training, primarily utilizing CT-based imaging.

Results

The rate of correct admission diagnosis was 91.1% (604/663) for acute cerebral ischemia (ischemic stroke/TIA), 99.2% (117/118) for hemorrhagic stroke, and 61.5% (144/234) for stroke mimics. Of the 150 (14.8%) misdiagnosed patients, 135 (90.0%) had no acute findings on initial imaging and 100 (67.6%) presented with NIH Stroke Scale score 0 to 2. Misdiagnosis altered medical management in 70 cases, including administration of unnecessary treatments (thrombolysis n = 13, other n = 24), omission of thrombolysis (n = 5), delays to specific treatments of stroke mimics (n = 13, median 56 [31–93] hours), and delays to antiplatelet medication (n = 14, median 1 [1–2] day). Misdiagnosis extended emergency department stay (median 6.6 [4.7–10.4] vs 5.8 [3.7–9.2] hours; p = 0.001) and led to unnecessary stroke unit stay (n = 10). Detailed review revealed 8 cases (0.8%) in which misdiagnosis was possible or likely to have worsened outcomes, but no death occurred as a result of misdiagnosis.

Conclusions

Our findings support the safety of highly optimized door-to-needle times, built on thorough training in a large-volume, centralized stroke service with long-standing experience. Augmented imaging and front-loaded specialist engagement are warranted to further improve rapid stroke diagnostics.

Intravenous thrombolysis for acute ischemic stroke: a bridge between two centuries

INTRODUCTION

Intravenous tissue-plasminogen activator (tPA) remains the only approved systemic reperfusion therapy suitable for most patients presenting timely with acute ischemic stroke. Accumulating real-word experience for over 20 years regarding tPA safety and effectiveness led to re-appraisal of original contraindications for intravenous thrombolysis (IVT). Areas covered: This narrative review focuses on fast yet appropriate selection of patients for safe administration of tPA per recently expanded indications. Novel strategies for rapid patient assessment will be discussed. The potential for mobile stroke units (MSU) that shorten onset-to-needle time and increase tPA treatment rates is addressed. The use of IVT in the era of non-vitamin K antagonist oral anticoagulants (NOACs) is highlighted. The continuing role of IVT in large vessel occlusion (LVO) patients eligible for mechanical thrombectomy (MT) is discussed with regards to 'drip and ship' vs. 'mothership' treatment paradigms. Promising studies of penumbral imaging to extend IVT beyond the 4.5-hour window and in wake-up strokes are summarized. Expert commentary: This review provides an update on the role of IVT in specific conditions originally considered tPA contraindications. Novel practice challenges including NOAC's, MSU proliferation and bridging therapy (IVT&MT) for LVO patients, and the potential extension of IVT time-window using penumbral imaging are emerging as safe and potentially effective IVT applications.

Clinical features of stroke mimics in the emergency department

Aim

To clarify the features of stroke mimics.

Methods

We retrospectively investigated stroke mimic cases among the suspected stroke cases examined at our emergency department, over the past 9 years, during the tissue‐type plasminogen activator treatment time window.

Results

Of 1,557 suspected acute stroke cases examined at the emergency department, 137 (8.8%) were stroke mimics. The most common causes were symptomatic epilepsy (28 cases, 20.4%), neuropathy‐like symptoms (21 cases, 15.3%), and hypoglycemia (15 cases, 10.9%). Outcomes were survival to hospital discharge for 91.2% and death for 8.8% of the cases. Clinical results were significantly different between stroke mimics and the stroke group for low systolic blood pressure, low National Institutes of Health Stroke Scale score on initial treatment, history of diabetes, and no history of arrhythmia. On multivariate analysis, distinguishing factors for stroke mimics include systolic blood pressure ≤ 140 mmHg, National Institutes of Health Stroke Scale score ≤ 5 points, history of diabetes, and no history of arrhythmia.

Conclusions

Frequency of stroke mimics in cases of acute stroke suspected cases is 8.8%, and the most common cause is epilepsy. In order to distinguish stroke mimics, it is useful to understand common diseases presenting as stroke mimics and evaluate clinical features different from stroke by medical interview or nerve examination.

Stroke Chameleons and Stroke Mimics in the Emergency Department

PURPOSE OF REVIEW

We discuss the frequency of stroke misdiagnosis in the emergency department (ED), identify common diagnostic pitfalls, describe strategies to reduce diagnostic error, and detail ongoing research.

RECENT FINDINGS

The National Academy of Medicine has re-defined and highlighted the importance of diagnostic errors for patient safety. Recent rates of stroke under-diagnosis (false-negative cases, "stroke chameleons") range from 2-26% and 30-43% for stroke over-diagnosis (false-positive cases, "stroke mimics"). Failure to diagnosis stroke can preclude time-sensitive treatments and has been associated with poor outcomes. Strategies have been developed to improve detection of posterior circulation stroke syndromes, but ongoing work is needed to reduce under-diagnosis in other atypical stroke presentations. The published rates of harm associated with stroke over-diagnosis, particularly thrombolysis of stroke mimics, remain low. Additional strategies to improve the accuracy of stroke diagnosis should focus on rapid clinical reasoning in the time-sensitive setting of acute ischemic stroke and identifying imperfections in the healthcare system which may contribute to diagnostic error.

Validation of simplified FABS scale to predict stroke mimics in a Chinese population undergoing intravenous thrombolysis

OBJECTIVES

A large number of suspected stroke patients undergoing intravenous thrombolysis are stroke mimics (SMs). In this study, we sought to revise the FABS scale for screening and stratifying SMs from acute ischemic stroke (AIS) in a Chinese stroke population receiving fibrinolytic therapy.

PATIENTS AND METHODS

The simplified FABS (sFABS) scale includes 4 items with 1 point for each item present: absence of facial droop, negative history of atrial fibrillation, age <50years, systolic blood pressure <150mm Hg at presentation. We evaluated consecutive suspected stroke patients undergoing intravenous thrombolysis in our stroke center for validation of sFABS scale. Diagnosis of SMs was based on absence of acute ischemic lesions on first and second diffusion weight imaging sequence in addition to an alternate diagnosis at discharge.

RESULTS

A total of 190 AIS patients and 28 SMs were included in this study from December 2015 to February 2017. The sFABS scale showed excellent discrimination (C statistic: 0.928, 95% CI: 0.887-0.969, P<0.001). The Hosmer and Lemeshow goodness of fit test showed that the sFABS scale also had a good calibration (Cox and Snell R²=0.294, Nagelkerke R²=0.549). The plot of observed versus predicted risk of SMs showed high correlation (Pearson correlation coefficient: 0.983) between observed and predicted risk in our registered stroke population.

CONCLUSION

The sFABS scale had excellent discrimination and good calibration abilities to predict SMs among a Chinese stroke population receiving tPA therapy. Further imaging evaluation may be necessary before the use of tPA if the sFABS score is higher.

Novel Screening Tool for Stroke Using Artificial Neural Network

Background and Purpose—

The timely diagnosis of stroke at the initial examination is extremely important given the disease morbidity and narrow time window for intervention. The goal of this study was to develop a supervised learning method to recognize acute cerebral ischemia (ACI) and differentiate that from stroke mimics in an emergency setting.

Methods—

Consecutive patients presenting to the emergency department with stroke-like symptoms, within 4.5 hours of symptoms onset, in 2 tertiary care stroke centers were randomized for inclusion in the model. We developed an artificial neural network (ANN) model. The learning algorithm was based on backpropagation. To validate the model, we used a 10-fold cross-validation method.

Results—

A total of 260 patients (equal number of stroke mimics and ACIs) were enrolled for the development and validation of our ANN model. Our analysis indicated that the average sensitivity and specificity of ANN for the diagnosis of ACI based on the 10-fold cross-validation analysis was 80.0% (95% confidence interval, 71.8–86.3) and 86.2% (95% confidence interval, 78.7–91.4), respectively. The median precision of ANN for the diagnosis of ACI was 92% (95% confidence interval, 88.7–95.3).

Conclusions—

Our results show that ANN can be an effective tool for the recognition of ACI and differentiation of ACI from stroke mimics at the initial examination.