The Accuracy of Large Vessel Occlusion Recognition Scales in Telestroke Setting

Abstract

Introduction: A significant proportion of acute ischemic stroke (AIS) patients who are evaluated through telestroke consultation are transferred to thrombectomy-capable stroke centers (TSCs) for concern of large vessel occlusion (LVO). Patient triage selection is commonly based on the clinical suspicion of LVO, which lacks specificity and could result in unnecessary transfers. In this study, we aimed to assess the accuracy of the most commonly used LVO recognition scales in telestroke setting. Methods: AIS patients transferred to TSCs for suspicion of an LVO were included in this retrospective study. Patients were evaluated by a stroke neurologist through a telestroke consult before transfer. The National Institute of Health Stroke Scale (NIHSS) score documented by the stroke neurologist was retrieved from medical records and used to calculate five other LVO recognition scales (Rapid Arterial Occlusion Evaluation Scale [RACE], Field Assessment Stroke Triage for Emergency Destination [FAST-ED], Cincinnati Prehospital Stroke Severity Scale [CPSSS], 3-item stroke scale [3I-SS], and Prehospital Acute Stroke Severity Scale [PASS]). We calculated the sensitivity, specificity, accuracy, positive and negative predictive values, false positive rate (FPR), and false negative rate (FNR) of each score using published cutoffs and then examined all possible cutoff values for each of these scales in addition to the NIHSS. Results: A total of 439 patients were included in the final analysis. A total of 48.5% of patients had an LVO confirmed on computed tomography angiogram. RACE score had the highest accuracy (78%). Overall, the five derived LVO recognition scores have at least 10% FNR. When examining all possible cutoff values, the NIHSS (cutoff of 6) had a 3% FNR but 73% FPR (false transfer). Conclusion: The use of the NIHSS and other LVO recognition scores over telestroke may result in unnecessary transfers. Better diagnostic tools that could maximize sensitivity with acceptable specificity are urgently needed.