Stroke etiologies in patients with COVID-19: the SVIN COVID-19 multinational registry

Author:

Ramos-Araque María E., ,Siegler James E.,Ribo Marc,Requena Manuel,López Cristina,de Lera Mercedes,Arenillas Juan F.,Pérez Isabel Hernández,Gómez-Vicente Beatriz,Talavera Blanca,Portela Pere Cardona,Guillen Ana Nuñez,Urra Xabier,Llull Laura,Renú Arturo,Nguyen Thanh N.,Jillella Dinesh,Nahab Fadi,Nogueira Raul,Haussen Diogo,Then Ryna,Thon Jesse M.,Esparragoza Luis Rodríguez,Hernández-Pérez Maria,Bustamante Alejandro,Mansour Ossama Yassin,Megahed Mohammed,Hassan Tamer,Liebeskind David S.,Hassan Ameer,Bushnaq Saif,Osman Mohamed,Vazquez Alejandro Rodriguez

Abstract

Abstract Background and purpose Coronavirus disease 2019 (COVID-19) is associated with a small but clinically significant risk of stroke, the cause of which is frequently cryptogenic. In a large multinational cohort of consecutive COVID-19 patients with stroke, we evaluated clinical predictors of cryptogenic stroke, short-term functional outcomes and in-hospital mortality among patients according to stroke etiology. Methods We explored clinical characteristics and short-term outcomes of consecutively evaluated patients 18 years of age or older with acute ischemic stroke (AIS) and laboratory-confirmed COVID-19 from 31 hospitals in 4 countries (3/1/20–6/16/20). Results Of the 14.483 laboratory-confirmed patients with COVID-19, 156 (1.1%) were diagnosed with AIS. Sixty-one (39.4%) were female, 84 (67.2%) white, and 88 (61.5%) were between 60 and 79 years of age. The most frequently reported etiology of AIS was cryptogenic (55/129, 42.6%), which was associated with significantly higher white blood cell count, c-reactive protein, and D-dimer levels than non-cryptogenic AIS patients (p</=0.05 for all comparisons). In a multivariable backward stepwise regression model estimating the odds of in-hospital mortality, cryptogenic stroke mechanism was associated with a fivefold greater odds in-hospital mortality than strokes due to any other mechanism (adjusted OR 5.16, 95%CI 1.41–18.87, p = 0.01). In that model, older age (aOR 2.05 per decade, 95%CI 1.35–3.11, p < 0.01) and higher baseline NIHSS (aOR 1.12, 95%CI 1.02–1.21, p = 0.01) were also independently predictive of mortality. Conclusions Our findings suggest that cryptogenic stroke among COVID-19 patients carries a significant risk of early mortality.

Publisher

Springer Science and Business Media LLC

Subject

Clinical Neurology,General Medicine

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