Determining ischemic stroke subtype: an improved algorithm and its use in a comprehensive stroke unit

Abstract

Objective ‒ to implement a inified algorithm for determining an ischemic cerebral stroke (ICS) etiological subtype and evaluate the results of its use in patients who were admitted to a comprehensive stroke unit (CSU).Materials and methods. The study enrolled 689 patients with ICS (43.4 % women, 56.6 % men; median age 68.1 years (59.7–75.5)) who in 2010 to 2018 were admitted to a hospital unit where the structure and processes correspond to the principles of CSU. The participants’ age, gender, National Institutes of Health Stroke Scale (NIHSS) and modified Rankin Scale scores were analyzed. All patients underwent an initial workup that included neuroimaging, vascular imaging, a cardiologist’s exam and a set of laboratory tests, and an advanced evaluation, at his physician discretion. All ICS was assigned to one of the four etiological subtypes: cardioembolic, atherosclerotic, lacunar or other. Results. According to the proposed algorithm, 294 (42.7 %) cases were assigned to cardioembolic subtype, 282 (40.9 %) to atherosclerotic subtype, 52 (7.5 %) to lacunar subtype and 61 (8.9 %) to ischemic cerebral stroke unknown etiology. Differences in the shown frequency of the main etiological ICS subtypes compared to the results of epidemiological studies are due to the greater severity of ICS in our sample: baseline median NIHSS total score was 10 (6–17), and median modified Rankin scale score was 4 (3–5), and, on the other hand, to in-depth assessment using modern diagnostic technologies and a longer length of stay that allowed for the tests to be completed.Conclusions. Thorough evaluation and the use of a unified algorithm based on causal etiological classifications allow to successfully determine an ICS subtype in the CSU patients with low proportion of ICS of unknown etiology, which is the key to effective secondary prevention.