Predictors of Cognitive Impairment After Stroke: A Prospective Stroke Cohort Study
Predictors of Cognitive Impairment After Stroke: A Prospective Stroke Cohort Study
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中风后认知障碍的预测因素：前瞻性中风队列研究
DOI：
10.3233/jad-190382
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发表时间：
2019-01-01
影响因子：
4
通讯作者：
Dong, Qiang
中科院分区：
文献类型：
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作者：
Ding, Meng-Yuan;Xu, Yi;Dong, Qiang
背景：中风后认知障碍（PSCI）显着影响中风幸存者的生活质量和康复。识别入院时认知能力下降的风险模型将有助于改善中风后患者的早期发现和管理。目的：为缺血性中风幸存者开发新的临床风险评分，以预测 6-12 个月的 PSCI。方法：我们前瞻性地纳入了 179 名在发病 7 天内诊断为急性缺血性中风的患者。根据基线人口统计、临床危险因素和放射学参数对数据进行分析。采用Logistic回归和受试者工作曲线下面积（AUROC）评估模型效率。结果：145名受试者完成了6-12个月的随访，77名患者（53.1%）被诊断为PSCI。年龄（β=0.065，OR=1.067，95%CI=1.016-1.120），受教育年限（β=-0.346，OR=0.707，95%CI=0.607-0.824），脑室周围高信号分级（β=1.253，OR=3.501，95%CI= 1.652-7.417）、糖尿病（β = 1.762，OR = 5.825，95% CI = 2.068-16.412）和急性非腔隙性梗塞数量（β = 0.569，OR = 1.766，95% CI = 1.243-2.510）与6-12个月PSCI，构建了预测效率最优的模型（AUC=0.884，95%CI=0.832-0.935）。结论：优化的风险模型能够以简单、实用的方式有效筛查6-12个月PSCI高风险的卒中幸存者。经过进一步独立的外部队列验证后，它可能成为临床实践早期识别 PSCI 高风险患者的潜在工具。
Background: Post-stroke cognitive impairment (PSCI) significantly affects stroke survivors' quality of life and rehabilitation. A risk model identifying cognitive decline at admission would help to improve early detection and management of post-stroke patients.Objective: To develop a new clinical risk score for ischemic stroke survivors in predicting 6-12 months PSCI.Methods: We prospectively enrolled 179 patients diagnosed with acute ischemic stroke within a 7-day onset. Data were analyzed based on baseline demographics, clinical risk factors, and radiological parameters. Logistic regression and area under the receiver operating curve (AUROC) were used to evaluate model efficiency.Results: One hundred forty-five subjects completed a 6-12-month follow-up visit, and 77 patients (53.1%) were diagnosed with PSCI. Age (beta = 0.065, OR= 1.067, 95% CI = 1.016-1.120), years of education (beta =-0.346, OR= 0.707, 95% CI = 0.607-0.824), periventricular hyperintensity grading (beta = 1.253, OR= 3.501, 95% CI = 1.652-7.417), diabetes mellitus (beta = 1.762, OR= 5.825, 95% CI = 2.068-16.412), and the number of acute nonlacunar infarcts (beta = 0.569, OR= 1.766, 95% CI = 1.243-2.510) were independently associated with 6-12 month PSCI, constituting a model with optimal predictive efficiency (AUC= 0.884, 95% CI = 0.832-0.935).Conclusions: The optimized risk model was effective in screening stroke survivors at high risk of developing 6-12 months PSCI in a simple and pragmatic way. It could be a potential tool to identify patients with a high risk of PSCI at an early stage in clinical practice after further independent external cohort validation.