网络影响评分是卒中后认知障碍的独立预测因子：2341 例急性缺血性卒中患者的多中心队列研究。
Network impact score is an independent predictor of post-stroke cognitive impairment: A multicenter cohort study in 2341 patients with acute ischemic stroke.
机构信息
Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, the Netherlands.
Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, the Netherlands.
出版信息
Neuroimage Clin. 2022;34:103018. doi: 10.1016/j.nicl.2022.103018. Epub 2022 Apr 27.
BACKGROUND
Post-stroke cognitive impairment (PSCI) is a common consequence of stroke. Accurate prediction of PSCI risk is challenging. The recently developed network impact score, which integrates information on infarct location and size with brain network topology, may improve PSCI risk prediction.
AIMS
To determine if the network impact score is an independent predictor of PSCI, and of cognitive recovery or decline.
METHODS
We pooled data from patients with acute ischemic stroke from 12 cohorts through the Meta VCI Map consortium. PSCI was defined as impairment in ≥ 1 cognitive domain on neuropsychological examination, or abnormal Montreal Cognitive Assessment. Cognitive recovery was defined as conversion from PSCI < 3 months post-stroke to no PSCI at follow-up, and cognitive decline as conversion from no PSCI to PSCI. The network impact score was related to serial measures of PSCI using Generalized Estimating Equations (GEE) models, and to PSCI stratified according to post-stroke interval (<3, 3-12, 12-24, >24 months) and cognitive recovery or decline using logistic regression. Models were adjusted for age, sex, education, prior stroke, infarct volume, and study site.
RESULTS
We included 2341 patients with 4657 cognitive assessments. PSCI was present in 398/844 patients (47%) <3 months, 709/1640 (43%) at 3-12 months, 243/853 (28%) at 12-24 months, and 208/522 (40%) >24 months. Cognitive recovery occurred in 64/181 (35%) patients and cognitive decline in 26/287 (9%). The network impact score predicted PSCI in the univariable (OR 1.50, 95%CI 1.34-1.68) and multivariable (OR 1.27, 95%CI 1.10-1.46) GEE model, with similar ORs in the logistic regression models for specified post-stroke intervals. The network impact score was not associated with cognitive recovery or decline.
CONCLUSIONS
The network impact score is an independent predictor of PSCI. As such, the network impact score may contribute to a more precise and individualized cognitive prognostication in patients with ischemic stroke. Future studies should address if multimodal prediction models, combining the network impact score with demographics, clinical characteristics and other advanced brain imaging biomarkers, will provide accurate individualized prediction of PSCI. A tool for calculating the network impact score is freely available at https://metavcimap.org/features/software-tools/lsm-viewer/.
背景
中风后认知障碍（PSCI）是中风的常见后果。准确预测 PSCI 风险具有挑战性。最近开发的网络影响评分，综合了梗塞部位和大小的信息以及脑网络拓扑结构，可能会提高 PSCI 风险预测的准确性。
目的
确定网络影响评分是否是 PSCI 的独立预测因子，以及认知恢复或下降的预测因子。
方法
我们通过 Meta VCI Map 联盟汇集了来自 12 个队列的急性缺血性中风患者的数据。PSCI 的定义为神经心理学检查中≥1个认知域受损，或蒙特利尔认知评估异常。认知恢复定义为从中风后 3 个月内的 PSCI 转为随访时无 PSCI，认知下降定义为从无 PSCI 转为 PSCI。使用广义估计方程（GEE）模型将网络影响评分与 PSCI 的连续测量值相关联，并使用逻辑回归根据中风后间隔（<3、3-12、12-24、>24 个月）和认知恢复或下降对 PSCI 进行分层。模型调整了年龄、性别、教育程度、既往中风、梗塞体积和研究地点。
结果
我们纳入了 2341 名患者的 4657 次认知评估。398/844 名患者（47%）<3 个月时有 PSCI，709/1640 名患者（43%）在 3-12 个月时有 PSCI，243/853 名患者（28%）在 12-24 个月时有 PSCI，208/522 名患者（40%）>24 个月时有 PSCI。181 名患者中有 64 名（35%）认知恢复，287 名患者中有 26 名（9%）认知下降。网络影响评分在单变量（OR 1.50，95%CI 1.34-1.68）和多变量（OR 1.27，95%CI 1.10-1.46）GEE 模型中预测 PSCI，在特定中风后间隔的逻辑回归模型中也具有相似的 OR。网络影响评分与认知恢复或下降无关。
结论
网络影响评分是 PSCI 的独立预测因子。因此，网络影响评分可能有助于更精确和个体化地预测缺血性中风患者的认知预后。未来的研究应探讨将网络影响评分与人口统计学、临床特征和其他先进的脑成像生物标志物相结合的多模态预测模型是否能提供 PSCI 的准确个体化预测。网络影响评分的计算工具可在 https://metavcimap.org/features/software-tools/lsm-viewer/ 免费获取。
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