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Evaluating Prehospital Stroke Scales for Large Vessel Occlusion: A Systematic Review and Network Meta-Analysis
Noah Lee Ahmad Nawabi1,2, Esteban Rivera Rivera3, Daniel de Wilde1
1Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
Background And Objectives:
Ischemic stroke remains a leading cause of death and disability worldwide, with large vessel occlusion (LVO) accounting for a disproportionate share of poststroke morbidity. Early identification of LVO is essential for timely intervention with endovascular thrombectomy; however, the clinical scales currently used for triage vary widely in their application and accuracy. This study assesses the diagnostic performance of clinical stroke scales in predicting LVO.
Methods:
A systematic review was conducted to identify studies evaluating the diagnostic accuracy of prehospital stroke scales for detecting LVO. Pooled sensitivity and specificity were estimated using a bivariate random-effects model, with diagnostic performance further assessed through summary receiver operating characteristic (ROC) curves and area under the curve (AUC) analysis. A Bayesian network meta-analysis was conducted to rank the scales using surface under the cumulative ranking (SUCRA) probabilities, and post hoc analyses were performed to evaluate publication bias.
Results:
A total of 58 studies comprising 58,381 patients and 33 unique stroke scales were included in the final analysis. The studies, published between 2014 and 2023, were primarily conducted in North America (50%) and Europe (26%), with a median sample size of 473 participants. Pooled sensitivity ranged from 0.30 (HEMIPARESIS) to 0.99 (LARIO) while specificity varied from 0.34 (FANG) to 0.94 (HEMIPLEGIA). Among the highest-performing scales overall were LARIO (AUC = 0.983), FPSS (AUC = 0.896), FACE2AD (AUC = 0.876), and ACT-FAST (AUC = 0.873). In prehospital settings, FPSS (AUC = 0.896), FAST VAN (AUC = 0.878), and FACE2AD (AUC = 0.876) demonstrated strong performance while LARIO (AUC = 0.983) and ACT-FAST (AUC = 0.883) showed the highest accuracy in hospital settings. Bayesian network meta-analysis identified POMONA (SUCRA = 0.877), NIHSS (0.856), sNIHSS EMS (0.854), G-FAST (0.823), and SAFE (0.788) as the top-ranked scales. Funnel plot analysis revealed minimal publication bias among the most frequently evaluated tools, including RACE, CPSS, and NIHSS.
Discussion:
Numerous clinical scales are available for detecting LVO in the prehospital setting. While several demonstrate strong performance in specific contexts, there remains a clear need for a simple, accurate, and generalizable tool to reliably identify patients with LVO across diverse clinical environments.
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