Brian S Katz1, Jason T McMullan2, Heidi Sucharew2, Opeolu Adeoye2, Joseph P Broderick2. 1. From the Department of Neurology (B.S.K., J.P.B.) and Department of Emergency Medicine (J.T.M., O.A.), University of Cincinnati, College of Medicine, OH; and Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, OH (H.S.). katzbs@ucmail.uc.edu. 2. From the Department of Neurology (B.S.K., J.P.B.) and Department of Emergency Medicine (J.T.M., O.A.), University of Cincinnati, College of Medicine, OH; and Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, OH (H.S.).
Abstract
BACKGROUND AND PURPOSE: We derived and validated the Cincinnati Prehospital Stroke Severity Scale (CPSSS) to identify patients with severe strokes and large vessel occlusion (LVO). METHODS: CPSSS was developed with regression tree analysis, objectivity, anticipated ease in administration by emergency medical services personnel and the presence of cortical signs. We derived and validated the tool using the 2 National Institute of Neurological Disorders and Stroke (NINDS) tissue-type plasminogen activator Stroke Study trials and Interventional Management of Stroke III (IMS III) Trial cohorts, respectively, to predict severe stroke (National Institutes of Health Stroke Scale [NIHSS]≥15) and LVO. Standard test characteristics were determined and receiver operator curves were generated and summarized by the area under the curve. RESULTS: CPSSS score ranges from 0 to 4; composed and scored by individual NIHSS items: 2 points for presence of conjugate gaze (NIHSS≥1); 1 point for presence of arm weakness (NIHSS≥2); and 1 point for presence abnormal level of consciousness commands and questions (NIHSS level of consciousness≥1 each). In the derivation set, CPSSS had an area under the curve of 0.89; score≥2 was 89% sensitive and 73% specific in identifying NIHSS≥15. Validation results were similar with an area under the curve of 0.83; score≥2 was 92% sensitive, 51% specific, a positive likelihood ratio of 3.3, and a negative likelihood ratio of 0.15 in predicting severe stroke. For 222 of 303 IMS III subjects with LVO, CPSSS had an area under the curve of 0.67; a score≥2 was 83% sensitive, 40% specific, positive likelihood ratio of 1.4, and negative likelihood ratio of 0.4 in predicting LVO. CONCLUSIONS: CPSSS can identify stroke patients with NIHSS≥15 and LVO. Prospective prehospital validation is warranted.
BACKGROUND AND PURPOSE: We derived and validated the Cincinnati Prehospital Stroke Severity Scale (CPSSS) to identify patients with severe strokes and large vessel occlusion (LVO). METHODS:CPSSS was developed with regression tree analysis, objectivity, anticipated ease in administration by emergency medical services personnel and the presence of cortical signs. We derived and validated the tool using the 2 National Institute of Neurological Disorders and Stroke (NINDS) tissue-type plasminogen activator Stroke Study trials and Interventional Management of Stroke III (IMS III) Trial cohorts, respectively, to predict severe stroke (National Institutes of Health Stroke Scale [NIHSS]≥15) and LVO. Standard test characteristics were determined and receiver operator curves were generated and summarized by the area under the curve. RESULTS:CPSSS score ranges from 0 to 4; composed and scored by individual NIHSS items: 2 points for presence of conjugate gaze (NIHSS≥1); 1 point for presence of arm weakness (NIHSS≥2); and 1 point for presence abnormal level of consciousness commands and questions (NIHSS level of consciousness≥1 each). In the derivation set, CPSSS had an area under the curve of 0.89; score≥2 was 89% sensitive and 73% specific in identifying NIHSS≥15. Validation results were similar with an area under the curve of 0.83; score≥2 was 92% sensitive, 51% specific, a positive likelihood ratio of 3.3, and a negative likelihood ratio of 0.15 in predicting severe stroke. For 222 of 303 IMS III subjects with LVO, CPSSS had an area under the curve of 0.67; a score≥2 was 83% sensitive, 40% specific, positive likelihood ratio of 1.4, and negative likelihood ratio of 0.4 in predicting LVO. CONCLUSIONS:CPSSS can identify strokepatients with NIHSS≥15 and LVO. Prospective prehospital validation is warranted.
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