•  
  •  
 

Article Title

Validation of Stroke Network of Wisconsin (SNOW) Scale at Aurora Health Care

Abstract

Background: The Stroke Network of Wisconsin (SNOW) scale, previously called the Pomona scale, was developed to predict large-vessel occlusions (LVO) in patients with acute ischemic stroke. The original study showed a high accuracy of this scale.

Purpose: We sought to externally validate the SNOW scale in an independent cohort.

Methods: The SNOW scale includes 3 items: gaze deviation, expressive aphasia, and neglect. The SNOW scale is positive if any one of these items is present. We retrospectively reviewed a large cohort of all acute stroke patients who presented within 24 hours after onset at Aurora Health Care (14 hospitals) from January 2015 to December 2016. We calculated SNOW scale, the Vision Aphasia and Neglect (VAN) scale, the Cincinnati Prehospital Stroke Severity Scale (CPSSS), the Los Angeles Motor Scale (LAMS), and the Prehospital Acute Stroke Severity (PASS) scale for all patients. The predictive performance of all scales and several National Institute of Health Stroke Scale (NIHSS) cutoffs ≥ 6 were determined and compared. LVO was defined by total occlusions involving the intracranial internal carotid artery, middle cerebral artery (M1), or basilar arteries.

Results: Among 2183 acute ischemic stroke patients, 1381 had vascular imaging and were included in the analysis. LVO was detected in 169 (12%). A positive SNOW scale had comparable accuracy to predict LVO as the CPSS and an NIHSS ≥ 6. With area under the receiver operating characteristics curve of 0.78, a positive SNOW scale had higher accuracy than VAN (0.67, P < 0.001), LAMS ≥ 4 (0.62, P < 0.001), and PASS ≥ 2 (0.69, P < 0.001). A positive SNOW scale had sensitivity of 0.80, specificity of 0.76 to predict LVO, positive predictive value of 0.31, and negative predictive value of 0.96 for the detection of LVO versus CPSS ≥ 2 of 0.64, 0.87, 0.41, and 0.95, respectively.

Conclusion: In our large stroke network cohort, the SNOW scale has promising sensitivity, specificity, and accuracy to predict LVO. Future prospective studies in both prehospital and emergency room settings are warranted.

 

Submitted

October 26th, 2018

Accepted

October 29th, 2018