Background: Stroke is one of the most common debilitating diseases. Although effective treatment is available, a golden time has been defined in this regard. Therefore, prompt action is needed to identify patients with stroke as soon as possible, even in the pre-hospital stage. In recent years, several clinical scales have been introduced for this purpose. We performed the present study to examine the accuracy of eight clinical scales in terms of stroke diagnosis. Methods: This multicenter diagnostic accuracy study was conducted in 2019. All patients older than 18 years who were admitted to the emergency department (ED) and underwent brain magnetic resonance imaging (MRI) for a suspected stroke were eligible. All data were gathered through a pre-prepared checklist consisting of three sections, using the clinical records of the patients. The first section of the checklist included basic characteristics and demographic data. The second part included physical examination findings of 19 items related to the 8 scales. The third part was dedicated to the final diagnosis based on the interpretation of brain MRI, which was considered the gold standard for the diagnosis of acute ischemic stroke (AIS) in the current study. Results: The data from 805 patients suspected of stroke were analyzed. In all, 463 patients (57.5%) were male. The participants' age was 6-95 years with a mean age of 66.9 years (SD = 13.9). Of all the registered patients, 562 (69.8%) had an AIS. The accuracy of screening tests was 63.0% to 84.4%. The sensitivity and specificity were 71.9% to 95.7% and 46.5% to 82.8%, respectively. Among all the screening tests, Los Angeles Pre-Hospital Stroke Screening (LAPSS) had the lowest sensitivity, and Medic Prehospital Assessment for Code Stroke (Med PACS) had the highest sensitivity. In addition, PreHospital Ambulance Stroke Test (PreHAST) had the lowest specificity and LAPSS had the highest specificity. Conclusion:Based on the findings of the present study, highly sensitive tests that can be used in this regard are Cincinnati Prehospital Stroke Scale (CPSS), Face-Arm-Speech-Time (FAST), and Med PACS, all of which have about 95% sensitivity. On the other hand, none of the studied tools were desirable (specificity above 95%) in any of the examined cut-offs.

OBJECTIVES: In this study, we aimed to investigate the accuracy of recognition of stroke in the Emergency Room (ROSIER) Scale in the diagnosis of patients with acute ischemic stroke (AIS) transferred to the emergency department (ED). METHODS: The present study was a multicenter study. Records from patients suspected of stroke, who referred to the ED were reviewed. Demographic, clinical, and diagnostic data were extracted and then entered in checklists. ROSIER Scale was used to evaluate the possible diagnosis in this study. The definitive diagnosis of a stroke was made based on neurologist's assessment and clinical and neuroimaging findings, mainly brain magnetic resonance imaging (MRI). Receiver operating characteristic (ROC) curve analysis was conducted for assessing the accuracy of ROSIER in discrimination of stroke. RESULTS: The data of 356 suspected stroke patients were analyzed. Of all, 186 patients (52.2%) were male, and the mean age was 65.2 (standard deviation = 14.0) years ranging from 26 to 95 years. One hundred and fifty-one patients (42.4%) had AIS based on the final diagnosis. The area under the ROC curve was 0.85. The best cutoff point for ROSIER scale was ≥1 with a sensitivity of 85.4% (95% confidence interval [CI]: 78.8, 90.6%) and specificity of 65.8% (95% CI: 58.9, 72.3%). CONCLUSION: Based on the findings, although the best cutoff point was the same as the original (derivation) study, its sensitivity (85.4% vs. 92%) and specificity (65.8% vs. 86%) were considerably lower.

Background: Andsberg et al. have recently introduced a novel scoring system entitled “PreHospital Ambulance Stroke Test (PreHAST)”, which helps to early identification of patients with acute ischemic stroke (AIS) even in prehospital setting. Its validity has not been assessed in a study yet, and the purpose of this study was to assess this scoring system on a larger scale to provide further evidence in this regard. Methods: This was a cross-sectional multi-center accuracy study, in which, sampling was performed prospectively. All patients over 18 years of age admitted to the emergency department (ED) and suspected as AIS cases were included. All required data were recorded in a form consisting of 3 parts: baseline characteristics, neurological examination findings required for calculating PreHAST score, and the ultimate diagnosis made from interpretation of their brain magnetic resonance imaging (MRI). Results: Data from 805 patients (57.5% men) with the mean age of 67.1 ± 13.6 years were analyzed. Of all the patients presenting with suspected AIS, 562 (69.8%) had AIS based on their MRI findings. At the suggested cut-off point (score ≥ 1), PreHAST had a specificity of 46.5% [95% confidence interval (CI): 40.1%-53.0%) and a sensitivity of 93.2% (95%CI: 90.8%-95.2%). Conclusion: According to the findings of our study, at the suggested cut-off point (score ≥ 1), PreHAST had 93.2% sensitivity and 46.5% specificity in detection of patients with AIS, which were somewhat different from those reported in the original study, where 100% sensitivity and 40% specificity were reported for this scoring system.

IntroductionImmediate diagnosis of stroke is crucial in reducing its morbidity and mortality rate. There are various pre-hospital assessment tools, such as the Prehospital Ambulance Stroke Test (PreHAST) and the Cincinnati Prehospital Stroke Scale (CPSS) used to identify stroke early in the chain of care. The aim of this study is to compare the accuracy of PreHAST with CPSS in diagnosing stroke.MethodsIn this diagnostic accuracy study patients with suspicion of stroke were included in this study. In CPSS, the criterion used to indicate stroke are facial droop, speech and arm drift. In PreHAST it is eye position, visual field, facial palsy, right and left arms paresis, right and left legs paresis, sensory and speech. After data collection, sensitivity and specificity were calculated using standard formulae. Different cut-off points for the best diagnostic accuracy were examined in both CPSS and PreHAST.ResultsIn this study, 883 patients were investigated. The results demonstrated that in CPSS, the highest specificity and sensitivity was for facial droop (84.9%) and arm drift (82.7%); and in PreHAST it was eye position (99.6%) and facial palsy (49.2%). The best predictor of stroke in CPSS with highest sensitivity (78.5%) and specificity (66%) was a cut-off point of 1.5 (AUC: 0.744) (p<0.01(. In PreHAST, the highest sensitivity (68.4%) was a cut-off point of 2.5 and the highest specificity (90.2%) was a cut-off point of 5.5 (AUC: 0.775) (p<0.01).ConclusionBoth PreHAST and CPSS are useful screening tools in the pre-hospital diagnosis of stroke. In addition to high sensitivity, these tests provide a grading system in which higher cut-off points lead to higher specificity.