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fNIRS Biomarkers for Stratifying Poststroke Cognitive Impairment: Evidence From Frontal and Temporal Cortex Activation

医学 逻辑回归 认知 蒙特利尔认知评估 内科学 多元统计 功能近红外光谱 多元分析 认知障碍 冲程(发动机) 听力学 前额叶皮质 精神科 工程类 统计 机械工程 数学
作者
Han Zhang,Kang He,Yu Zhao,Yi Peng,Danling Feng,Jing Wang,Qiang Gao
出处
期刊:Stroke [Lippincott Williams & Wilkins]
标识
DOI:10.1161/strokeaha.124.050269
摘要

Poststroke cognitive impairment (PSCI) affects 30% to 50% of stroke survivors, severely impacting functional outcomes and quality of life. This study uses functional near-infrared spectroscopy (fNIRS) to assess task-evoked brain activation and its potential for stratifying the severity in patients with PSCI. A cross-sectional study was conducted at Nanchong Central Hospital between June 2023 and April 2024. The Montreal Cognitive Assessment was used to evaluate cognitive function. Hemodynamic responses, including oxygenated hemoglobin concentration signals from the frontal and temporal cortices, were measured using fNIRS. Healthy controls were recruited from the local community, matched to the patient group by age and sex. Univariate and multivariate linear regression analyses were performed to assess the correlations between fNIRS features, clinical variables, and group classifications. Significant fNIRS features and clinical variables were then identified and included in a logistic regression model. The final model was developed using a stratified approach based on the severity of cognitive impairment, and the predictive performance was evaluated using receiver operating characteristic analysis. A total of 159 participants were included: 138 patients with PSCI and 21 healthy controls. Patients with PSCI (mean age=53.7, SD=10.2 years, 78.3% male) exhibited significantly reduced oxygenated hemoglobin responses in the left dorsal prefrontal cortex (L-DPFC) compared with healthy controls (mean age=52.8, SD=4.7 years, 76.2% male). Patients were in the subacute to chronic phase poststroke. A multivariate model combining L-DPFC features distinguished PSCI from healthy controls (area under the curve, 0.76). For severity stratification, a model distinguishing mild from moderate PSCI (area under the curve, 0.75 [95% CI, 0.65-0.85]) included age, education level, National Institutes of Health Stroke Scale score, recanalization therapy, and L-DPFC centroid. A model distinguishing moderate from severe PSCI (area under the curve, 0.84 [95% CI, 0.75-0.92]) included disease duration, lesion location, and L-DPFC centroid. This study revealed that individuals with PSCI exhibited significantly reduced cortical activation in the L-DPFC compared with healthy controls. fNIRS features, particularly L-DPFC centroid values combined with clinical variables, effectively stratify PSCI severity. These findings may inform individualized rehabilitation strategies.
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