Identification Of Stroke Mimics Research Articles

Transient Ischaemic attack Emergency Referral (TIER): randomised feasibility trial results

BackgroundEarly assessment of patients with suspected transient ischaemic attack (TIA) is crucial to provision of effective care, including initiation of preventive therapies and identification of stroke mimics. Many patients with...

Role of Neurologists in Stroke Treatment

Determination of indications for acute reperfusion therapy (intravenous recombinant tissue plasminogen activator administration and mechanical thrombectomy) and identification of stroke mimics and chameleons are essential components of effective stroke treatment. Moreover, neurologists select the appropriate medications and manage the patient's general condition. Therefore, a neurologist's solid diagnostic skills based on neurological symptomatology and an internist's broad knowledge and insight play key roles clinically.

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.

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

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

External validation of stroke mimic prediction scales in the emergency department

BackgroundAcute 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.MethodsWe 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.ResultsTelestroke 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).ConclusionFour 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.

Abstract 175: Kaiser Stroke Express Program - Population Based Estimate of Potential Accuracy of Field Based Identification of Endovascular Treatment Candidates

Background: Whether patients with acute stroke and large vessel occlusion (LVO) may benefit from prehospital identification and diversion by EMS to a center offering endovascular therapy (EST) is controversial. The accuracy of prehospital scales as predictors of LVO is only one feature of whether EMS can effectively identify patients suitable for EST. Other factors include accuracy of last known well time (LTKW) and identification of stroke mimics. We performed a population-based estimate of potential accuracy of field based identification of potential EST candidates in a large community setting. Methods: In Kaiser Permanente Northern California, all acute stroke patients arriving at its 19 primary stroke centers (PSC) between 7am and 12am were evaluated on arrival by stroke neurologists by video. We reviewed the teleneurology notes to determine the potential accuracy of EST selection based on NIHSS score > 7. Results: For 2016, there were 2546 total potential stroke alerts triaged by EMS as having potential acute strokes [Figure]. Of these, 1268 (50%) were not candidates for acute stroke treatment for various reasons including stroke mimics and inaccurate LTKW. Out of 1241 cases deemed candidates for acute stroke treatment, 638 (25.1%) had potential LVO based on NIHSS > 7. Of these, 116 (4.6% of total “potential strokes” and 18.2% of patients who had “severe” strokes) were diagnosed with LVO and treated with EST. Conclusions: Even if field based tools were as accurate as clinical scoring by stroke neurologists, less than 1 in 4 patients diverted to endovascular stroke centers and away from closer PSC would benefit by receiving EST. Given that 50% of patients triaged by EMS did not qualify for any acute stroke treatment, a lower percentage of patients would actually benefit from field based diversion. Stroke systems may be better served by focusing on rapid treatment, evaluation, and transfer to endovascular centers than field based diversion strategies.

Contribution of EEG in transient neurological deficits.

Identification of stroke mimics and 'chameleons' among transient neurological deficits (TND) is critical. Diagnostic workup consists of a brain imaging study, for a vascular disease or a brain tumour and EEG, for epileptiform discharges. The precise role of EEG in this diagnostic workup has, however, never been clearly delineated. However, this could be crucial in cases of atypical or incomplete presentation with consequences on disease management and treatment. We analysed the EEG patterns on 95 consecutive patients referred for an EEG within 7days of a TND with diagnostic uncertainty. Patients were classified at the discharge or the 3-month follow-up visit as: 'ischemic origin', 'migraine aura', 'focal seizure', and 'other'. All patients had a brain imaging study. EEG characteristics were correlated to the TND symptoms, imaging study, and final diagnosis. Sixty four (67%) were of acute onset. Median symptom duration was 45min. Thirty two% were 'ischemic', 14% 'migraine aura', 19% 'focal seizure', and 36% 'other' cause. EEGs were recorded with a median delay of 1.6day after symptoms onset. Forty EEGs (42%) were abnormal. Focal slow waves were the most common finding (43%), also in the ischemic group (43%), whether patients had a typical presentation or not. Epileptiform discharges were found in three patients, one with focal seizure and two with migraine aura. Non-specific EEG focal slowing is commonly found in TND, and may last several days. We found no difference in EEG presentation between stroke mimics and stroke chameleons, and between other diagnoses.

A survey of UK paramedics’ views about their stroke training, current practice and the identification of stroke mimics

A survey of UK paramedics’ views about their stroke training, current practice and the identification of stroke mimics

Impact on patient management of the implementation of a magnetic resonance imaging dedicated to neurological emergencies.

Neurological emergencies consumed a high amount of resources in emergency department (ED). We aimed to study the effect of the implementation of a magnetic resonance imaging (MRI) dedicated to emergencies on the management of patients admitted in ED for neurological emergencies. We enrolled consecutive patients who underwent computed tomography and/or MRI for neurological disorders categorized as the suspicion of stroke and other reasons, over 2 periods that differed according to the priority access to computed tomography in the first period versus priority access to MRI in the second one. Criteria used to evaluate the effectiveness of the management were door-to-imaging time, ED length of stay, diagnostic performance, patient orientation, and length of hospitalization stay. When priority access to MRI, the door-to-imaging time was 31minutes longer (P=.005) for patients suspected of stroke or transient ischaemic attack (TIA) and 70minutes for the others (P<.001). The ED length of stay was 42minutes shorter (P=.013) for stroke/TIA patients and 26minutes longer (P=.029) for other patients. The proportion of patients with stroke mimics (no stroke amongst suspected stroke/TIA) increased (16.7% vs 25.6%, P=.017) as well as discharged patients (21.6% vs 29.6%, P=.002). The proportion of patients with stroke/TIA amongst other reasons of admission remained unchanged (P=.114). The median length of hospitalization stay decreased from 9 to 7days for the stroke/TIA patients (P=.042). The implementation of a MRI optimized the quality of care and diagnostic accuracy for patients admitted in ED with a better identification of stroke mimics, avoiding unnecessarily hospitalizations. The management of stroke-TIA patients was not modified, but their length of hospital stay reduced.

Use of Perfusion Imaging and Other Imaging Techniques to Assess Risks/Benefits of Acute Stroke Interventions

The advent of multimodal neuroimaging has provided acute stroke care providers with an armamentarium of sophisticated imaging options to utilize for guidance in clinical decision-making and management of acute ischemic stroke patients. Here, we propose a framework and potential algorithm-based methodology for imaging modality selection and utilization for the purpose of achieving optimal stroke clinical care. We first review imaging options that may best inform decision-making regarding revascularization eligibility, with a focus on the imaging modalities that best identify critical inclusion and exclusion criteria. Next, we review imaging methods that may guide the successful achievement of revascularization once it has been deemed desirable and feasible. Further, we review imaging modalities that may best assist in both the noninterventional care of acute stroke as well as the identification of stroke-mimics. Finally, we review imaging techniques under current investigation that show promise to improve future acute stroke management.

Identification of stroke mimics in the emergency department setting.

Previous studies have shown a stroke mimic rate of 9%-31%. We aimed to establish the proportion of stroke mimics amongst suspected acute strokes, to clarify the aetiology of stroke mimic and to develop a prediction model to identify stroke mimics. This was a retrospective cohort observational study. Consecutive "stroke alert" patients were identified over nine months in a primary stroke centre. 31 variables were collected. Final diagnosis was defined as "stroke" or "stroke mimic". Multivariable regression analysis was used to define clinical predictors of stroke mimic. 206 patients were reviewed. 22% were classified as stroke mimics. Multivariable scoring did not help in identification of stroke mimics. 99.5% of patients had a neurological diagnosis at final diagnosis. 22% of patients with suspected acute stroke had a stroke mimic. The aetiology of stroke mimics was varied, with seizure, encephalopathy, syncope and migraine being commonest. Multivariable scoring for identification of stroke mimics is not feasible. 99.5% of patients had a neurological diagnosis. This strengthens the case for the involvement of stroke neurologists/stroke physicians in acute stroke care.