Validation of the Ultimate Stroke Scale (USS): A standardized tool for automated large vessel occlusion screening

BackgroundPrehospital stroke screening for large vessel occlusions (LVOs) varies across institutions. This study compares manual stroke scale calculations against e-calculated scores using the Ultimate Stroke Scale (USS), a software automating multiple screening scales from a modified National Institutes of Health Stroke Scale (NIHSS) with a hand grip. The USS aims to streamline screening by computing multiple validated stroke scales simultaneously to enhance predictive value.MethodsWe applied eight stroke screening scales (NIHSS; Balance, Eyes, Face, Arms, Speech, and Time [BE-FAST]; Vision, Aphasia, Neglect; Los Angeles Motor Scale [LAMS]; Face, Arm, Speech, Time, Eye Deviation and Denial/Neglect [FAST-ED]; Emergency Medical Services Rapid Arterial oCclusion Evaluation [EMS RACE]; 3-Item Stroke Scale [3-ISS]; and Prehospital Acute Stroke Severity [PASS]) to 199 stroke activations between January 2021 and December 2023. In this prospective, external validation study, data were utilized from a previously published head-to-head comparison of multiple LVO scales for both LVOs and medium vessel occlusions which collected scales manually. We recalculated these scales using the USS and evaluated agreement (Kendall's τ) and diagnostic accuracy (ROC curves).ResultsThe USS showed strong to moderate agreement with manual calculations across all scales displayed by Kendall's τ correlation coefficients ranging from 0.549 to 0.931 (all p < 0.001). The BE-FAST had the lowest agreement (τ = 0.549), while PASS had the highest (τ = 0.931), followed by LAMS (τ = 0.894) and FAST-ED (τ = 0.864). Diagnostic accuracy was comparable between manual methods (area under the curve [AUC]: 0.590-0.743) and the USS (AUC: 0.575-0.758). The BE-FAST had the lowest AUC for both, LAMS had the highest for manual, and FAST-ED had the highest from the USS.ConclusionThe USS demonstrates potential as a reliable tool for automated stroke screening with consistent performance compared to manual methods.