Numerical Cincinnati Stroke Scale versus Stroke Severity Screening Tools for the Prehospital Determination of Large Vessel Occlusion.

Autor:	Wagstaff HM; Department of Emergency Medicine, University of Utah, 30 N. Mario Capecchi, HELIX Bldg, Level 2 South, Salt Lake City, UT 84112., Crowe RP; ESO: Emergency Medical Services Software, 11500 Alterra Pkwy #100, Austin, TX 78758., Youngquist ST; Department of Emergency Medicine, University of Utah, 30 N. Mario Capecchi, HELIX Bldg, Level 2 South, Salt Lake City, UT 84112., Stoecklein HH; Emergency Medicine of Jackson Hole, St. Johns Health, 625 E Broadway Ave, Jackson, WY 83001., Treichel A; ESO: Emergency Medical Services Software, 11500 Alterra Pkwy #100, Austin, TX 78758., He Y; Department of Neurology, University of Utah, 175 Medical Dr N, Salt Lake City, UT 84132., Majersik JJ; Department of Neurology, University of Utah, 175 Medical Dr N, Salt Lake City, UT 84132.
Jazyk:	angličtina
Zdroj:	Prehospital emergency care [Prehosp Emerg Care] 2024 Nov 19, pp. 1-12. Date of Electronic Publication: 2024 Nov 19.
DOI:	10.1080/10903127.2024.2430442
Abstrakt:	Objectives: Previous research demonstrated that the numerical Cincinnati Prehospital Stroke Scale (CPSS) identifies large vessel occlusion (LVO) at similar rates compared to dedicated LVO screening tools. We aimed to compare numerical CPSS to additional stroke scales using a national Emergency Medical Services (EMS) database. Methods: Using the ESO Data Collaborative, the largest EMS database with linked hospital data, we retrospectively analyzed prehospital patient records from 2022. Each EMS record was linked to corresponding emergency department (ED) and inpatient records through a data exchange platform. Prehospital CPSS was compared to the Cincinnati Stroke Triage Assessment Tool (C-STAT), the Field Assessment Stroke Triage for Emergency Destination (FAST-ED), and the Balance Eyes Face Arm Speech Time (BE-FAST). The optimal prediction cut points for LVO screening were determined by intersecting the sensitivity and specificity curves for each scale. To compare the discriminative abilities of each scale among those diagnosed with LVO, we used the area under the receiver operating curve (AUROC). Results: We identified 17,442 prehospital records from 754 EMS agencies with ≥ 1 documented stroke scale of interest: 30.3% (n = 5,278) had a hospital diagnosis of stroke, of which 71.6% (n = 3,781) were ischemic; of those, 21.6% (n = 817) were diagnosed with LVO. CPSS score ≥ 2 was found to be predictive of LVO with 76.9% sensitivity, 68.0% specificity, and AUROC 0.787 (95% CI 0.722-0.801). All other tools had similar predictive abilities, with sensitivity/specificity/AUROC of: C-STAT 62.5%/76.5%/0.727 (0.555-0.899); FAST-ED 61.4%/76.1%/0.780 (0.725-0.836); BE-FAST 70.4%/67.1%/0.739 (0.697-0.788). Conclusions: The less complex CPSS exhibited comparable performance to three frequently employed LVO detection tools. The EMS leadership, medical directors, and stroke system directors should weigh the complexity of stroke severity instruments and the challenges of ensuring consistent and accurate use when choosing which tool to implement. The straightforward and widely adopted CPSS may improve compliance while maintaining accuracy in LVO detection.
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu