■尽管白质高强度(WMH)与小血管闭塞(SVO)中风具有相似的血管风险和病理,很少有研究评估WMH容量负担对SVO卒中早期和延迟卒中结局的影响.
■使用多中心注册表数据库,我们纳入了2013年8月至2022年11月的SVO卒中患者.WMH量是通过使用深度学习的自动化方法估算的(VUNOMed-DeepBrain,首尔,韩国),这是一个商业上可用的分割模型。在倾向得分匹配(PSM)之后,我们评估了WMH体积对早期神经功能恶化(END)和不良功能结局的影响,并采用3个月改良的排名量表(mRS),定义为3个月时MRS评分>2,在SVO中风后。
■在1718例SVO中风病例中,重度WMH(Fazekas评分≥3)受试者的患病率为68.9%.PSM之后,重度WMH组3个月mRS(mRS>2)时的END和不良功能结局较高(END:6.9vs.13.5%,p<0.001;3个月mRS>2:11.4vs.24.7%,p<0.001)。使用PSM队列的逻辑回归分析显示,总WMH体积增加了END的风险[奇数比[OR],95%置信区间[CI];1.01,1.00-1.02,p=0.048],3个月mRS>2(OR,95%CI;1.02,1.01-1.03,p<0.001)。深WMH与END和3个月mRS>2相关,但室周WMH仅与3个月mRS>2相关。
■本研究使用深度学习分割模型的自动化方法来评估WMH负担对SVO卒中结局的影响。我们的研究结果强调了WMH负担在SVO卒中预后中的意义,鼓励量身定制的干预措施,以改善患者护理。
UNASSIGNED: Although white matter hyperintensity (WMH) shares similar vascular risk and pathology with small vessel occlusion (SVO) stroke, there were few studies to evaluate the impact of the burden of WMH volume on early and delayed stroke outcomes in SVO stroke.
UNASSIGNED: Using a multicenter registry database, we enrolled SVO stroke patients between August 2013 and November 2022. The WMH volume was estimated by automated methods using deep learning (VUNO Med-DeepBrain, Seoul, South Korea), which was a commercially available segmentation model. After propensity score matching (PSM), we evaluated the impact of WMH volume on early neurological deterioration (END) and poor functional outcomes at 3-month modified Ranking Scale (mRS), defined as mRS score >2 at 3 months, after an SVO stroke.
UNASSIGNED: Among 1,718 SVO stroke cases, the prevalence of subjects with severe WMH (Fazekas score ≥ 3) was 68.9%. After PSM, END and poor functional outcomes at 3-month mRS (mRS > 2) were higher in the severe WMH group (END: 6.9 vs. 13.5%, p < 0.001; 3-month mRS > 2: 11.4 vs. 24.7%, p < 0.001). The logistic regression analysis using the PSM cohort showed that total WMH volume increased the risk of END [odd ratio [OR], 95% confidence interval [CI]; 1.01, 1.00-1.02, p = 0.048] and 3-month mRS > 2 (OR, 95% CI; 1.02, 1.01-1.03, p < 0.001). Deep WMH was associated with both END and 3-month mRS > 2, but periventricular WMH was associated with 3-month mRS > 2 only.
UNASSIGNED: This study used automated methods using a deep learning segmentation model to assess the impact of WMH burden on outcomes in SVO stroke. Our findings emphasize the significance of WMH burden in SVO stroke prognosis, encouraging tailored interventions for better patient care.