The Addition of Atrial Fibrillation to the Los Angeles Motor Scale May Improve Prediction of Large Vessel Occlusion. Issue 4 (22nd March 2019)

• Record Type: Journal Article
• Authors: Narwal, Priya; Chang, Andrew D.; Grory, Brian Mac; Jayaraman, Mahesh; Madsen, Tracy; Paolucci, Gino; Cutting, Shawna; Burton, Tina; Dakay, Katarina; Schomer, Ashley; Rostanski, Sara; Noorian, Ali Reza; Nour, May; Liebeskind, David S.; Saver, Jeffrey; Furie, Karen; Yaghi, Shadi
• Is Part Of: Journal of neuroimaging. Volume 29:Issue 4(2019)
• Page Start: 463
• Page End: 466
• Publication Date: 2019-03-22
• Subjects: LAMS -- atrial fibrillation -- stroke -- large vessel occlusion -- thrombectomy; Diagnostic imaging -- Periodicals; Nervous system -- Diseases -- Diagnosis -- Periodicals; Imagerie pour le diagnostic -- Périodiques; Système nerveux -- Maladies -- Diagnostic -- Périodiques; Imagerie médicale; Neuroimagerie; Neurologie; Système nerveux; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.804754
• DOI: 10.1111/jon.12613
• Languages: English
• ISSNs: 1051-2284

Abstract

ABSTRACT: BACKGROUND AND PURPOSE: There is evidence suggesting that Los Angeles Motor Scale (LAMS) ≥ 4 predicts large vessel occlusion (LVO). We aim to determine whether atrial fibrillation (AF) can improve the ability of LAMS in predicting LVO. METHODS: We included consecutive patients with a discharge diagnosis of ischemic stroke admitted within 24 hours from last known normal time who underwent emergent vascular imaging using a computerized tomography angiography (CTA) of the head and neck. LVO was defined as intracranial internal carotid artery, proximal middle cerebral artery (M1 or proximal M2 segment), or basilar occlusion. LAMS was determined in the emergency department upon arrival. Univariate and multivariable models were performed to identify predictors of LVO and to determine whether AF improves the ability of LAMS to predict LVO. RESULTS: Among 1, 234 patients admitted with ischemic stroke, 862 underwent emergent vascular imaging (69.8%) out of which 374 (43.4%) had evidence of LVO and 207 (24%) underwent mechanical thrombectomy. In multivariable models, predictors of LVO were LAMS (OR 1.42 per one point increase 95% CI 1.29‐1.57) and AF (OR 1.95 95% CI 1.26‐3.02, P < .001). We developed the LAMS‐AF that includes the LAMS score and adds two points if AF is present. In this analysis, LAMS‐AF (AUC .78) had improved prediction over LAMS (AUC .76) in predicting LVO and lead to reclassification of 8/68 patients (11.8%) with LAMS = 3 group into the high‐risk LVO group. CONCLUSION: In patients with LAMS = 3, using the LAMS‐AF score may improve the ability of LAMS in predicting LVO. Larger studies are needed to confirm our findings.