In:
Stroke, Ovid Technologies (Wolters Kluwer Health), Vol. 53, No. Suppl_1 ( 2022-02)
Abstract:
Purpose: The usefulness of the existing risk stratification tools for atrial fibrillation (AF) is limited in predicting stroke recurrence in patients with acute ischemic stroke (AIS). Neuroimaging parameters obtained from diagnostic work-up of AIS could offer more elaborate prediction. Methods: A multicenter prospective cohort of AIS patients with AF recruited from 14 university hospitals or regional stroke centers were followed up for recurrent ischemic stroke (RIS) and a composite of all stroke and TIA. Neuroimaging features were derived from acute and chronic infarction patterns, and SVD markers such as lacunes, CMBs, and WMH. Cumulative incidences according to each neuroimaging parameter were estimated and compared using the Kaplan-Meier method with log-rank test and multivariable cause-specific hazard models with death as a competing risk. Results: A total of 2,270 patients were followed up for 431 days (IQR, 365-735), during which 111 RISs and 130 composite outcomes occurred. In unadjusted analysis, lesion multiplicity among acute infarction patterns, the presence of chronic non-lacunar infarction, and the presence of lacunes among SVD markers increased the risk of RIS significantly (Table). Other neuroimaging features such as territory multiplicity and location, confluency, topography, and size of acute lesions, lesion multiplicity, territory multiplicity, confluency, topography, and size of chronic infarction, number of lacunes, presence of CMBs, and WMH did not affect the incidence of RIS. The adjusted hazard ratios of lesion multiplicity of acute infarction, chronic infarction and lacunes were 1.45 (95% CI, 0.99-2.11), 1.57 (1.06-2.34) and 1.97 (1.30-2.98) for RIS, respectively. Similar findings were obtained for the composite outcome. Conclusions: Several neuroimaging markers were associated with recurrent ischemic stroke in AIS with AF. This could pave the way to a new stratification scheme for AF including neuroimaging parameters.
Type of Medium:
Online Resource
ISSN:
0039-2499
,
1524-4628
DOI:
10.1161/str.53.suppl_1.WP184
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2022
detail.hit.zdb_id:
1467823-8
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