国家神经系统疾病临床医学研究中心数据管理与共享系统

发表杂志：Journal of the American Heart Association

发表类型: Article

影响因子(IF): 5.4

PMID: 10.1161/JAHA.123.033616 Pubmed原文链接 全文下载

China is the hardest-hit area of stroke. Although there are active treatment strategies such as intravenous thrombolysis and arterial thrombectomy, some patients still remain functional disabilities. The difference in functional prognosis after stroke partly depends on infarction patterns, but the related mechanism is not clear. Inflammatory response is involved in the clinical outcome after stroke, and interleukin-6 plays a central role. It is reported that infarction regions may be the key factor affecting inflammatory response. In view of the correlation between infarction patterns, inflammation and prognosis after stroke, we hypothesize that infarction location could affect clinical outcomes by influencing the inflammatory response to some extent. In this study, we explore the association between infarction patterns and stroke prognosis as well as inflammatory response, and calculate the mediating effect value of certain inflammatory biomarkers, which would be beneficial for predicting functional outcomes after stroke and guiding clinical application of anti-inflammatory drugs.

Using Harvard-Oxford atlas, John-Hopkins University atlas and cerebellum atlas, we divided the whole brain into 139 regions in total. The non-negative matrix factorization（NMF）was used to process the previously constructed brain regions according to their anatomical locations, so as to obtain more realistic infarction patterns, which could better analyze research results from the perspective of clinical events. Then, we used the Bayesian linear regression model to calculate the relationship between infarction patterns and regions and functional outcomes, and found special patterns and regions which were the most relevant with clinical prognosis. Whereafter, we explored the correlation between these patterns and regions and inflammatory responses, and calculated the mediation effect value of inflammatory responses to prognosis after stroke. Finally, we aim to build a prediction model of stroke prognosis to guide the clinical practice.