Pomona Large Vessel Occlusion Screening Tool for Prehospital and Emergency Room Settings
Document Type
Article
Publication Date
2018
Publisher
Karger
Source Publication
Interventional Neurology
Source ISSN
1664-9737
Original Item ID
DOI: 10.1159/000486515
Abstract
Background: Early identification of patients with acute ischemic strokes due to large vessel occlusions (LVO) is critical. We propose a simple risk score model to predict LVO. Method: The proposed scale (Pomona Scale) ranges from 0 to 3 and includes 3 items: gaze deviation, expressive aphasia, and neglect. We reviewed a cohort of all acute stroke activation patients between February 2014 and January 2016. The predictive performance of the Pomona Scale was determined and compared with several National Institutes of Health Stroke Scale (NIHSS) cutoffs (≥4, ≥6, ≥8, and ≥10), the Los Angeles Motor Scale (LAMS), the Cincinnati Prehospital Stroke Severity (CPSS) scale, the Vision Aphasia and Neglect Scale (VAN), and the Prehospital Acute Stroke Severity Scale (PASS). Results: LVO was detected in 94 of 776 acute stroke activations (12%). A Pomona Scale ≥2 had comparable accuracy to predict LVO as the VAN and CPSS scales and higher accuracy than Pomona Scale ≥1, LAMS, PASS, and NIHSS. A Pomona Scale ≥2 had an accuracy (area under the curve) of 0.79, a sensitivity of 0.86, a specificity of 0.70, a positive predictive value of 0.71, and a negative predictive value of 0.97 for the detection of LVO. We also found that the presence of either neglect or gaze deviation alone had comparable accuracy of 0.79 as Pomona Scale ≥2 to detect LVO. Conclusion: The Pomona Scale is a simple and accurate scale to predict LVO. In addition, the presence of either gaze deviation or neglect also suggests the possibility of LVO.
Recommended Citation
Singh, Maharaj, "Pomona Large Vessel Occlusion Screening Tool for Prehospital and Emergency Room Settings" (2018). College of Nursing Faculty Research and Publications. 1121.
https://epublications.marquette.edu/nursing_fac/1121
Comments
Interventional Neurology, Vol. 7, No. 3-4 (2018):196-203. DOI.