Department of Neurology, The First Affiliated Hospital of Soochow University, No.899 Pinghai Road, Suzhou, Jiangsu 215006, China.
Department of Neurology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, No. 136 Jingzhou Road, Xiangyang, Hubei 441000, China.
J Stroke Cerebrovasc Dis. 2022 Jul;31(7):106515. doi: 10.1016/j.jstrokecerebrovasdis.2022.106515. Epub 2022 Apr 28.
Cognitive impairment is a common symptom after ischemic stroke. Such symptom can cause effect on rehabilitation of patients and their quality of life and. As stroke rapidly growth on nowadays, a reliable scoring tool to detect the risk of cognitive impairment after stroke is now being put on the first place.
We enrolled patients with acute ischemic stroke (AIS) as samples and hospitalized all at the First Affiliated Hospital of Soochow University between October 2018 and June 2020. All patients were assessed by the Montreal Cognitive Assessment (MoCA) scales and MoCA score < 26 was defined as standard to have having cognitive impairment. All patients were randomly (7:3) divided into two cohorts: the primary ones and the validated ones. Based on multivariate logistic model, the independent predictors of cognitive impairment in the acute phase were identified. The predictive nomogram was generated and evaluated by Harrell's concordance index (C-index) and calibration plot both in two cohorts, respectively.
A total of 191 patients were enrolled, of whom 135 comprised the primary cohort and 56 comprised the validated cohort. Gender, age, baseline NIHSS score, hyperhomocysteinemia (HHcy) and multiple lesions were independently associated with acute cognitive impairment after stroke and included to construct the nomogram. The nomogram derived from the primary cohort had an Area Under Curve (AUC) of 0.773 and the validated ones had an AUC of 0.859. Calibration plot revealed adequate fit of the nomogram in predictive value.
The new nomogram based on gender, age, baseline NIHSS score, HHcy and multiple lesions gave rise to an accurate and comprehensive prediction for cognitive impairment in AIS patients. After further validation, it could potentially be a reliable forecasting tool.
认知障碍是缺血性中风后的常见症状。这种症状会影响患者的康复和生活质量。由于如今中风的发病率迅速上升，因此现在急需一种可靠的评分工具来检测中风后认知障碍的风险。
我们招募了急性缺血性中风（AIS）患者作为样本，并于 2018 年 10 月至 2020 年 6 月在苏州大学第一附属医院住院。所有患者均采用蒙特利尔认知评估量表（MoCA）进行评估，MoCA 评分<26 定义为认知障碍。所有患者均随机（7:3）分为两组：主要组和验证组。基于多变量逻辑模型，确定了急性期认知障碍的独立预测因子。生成并分别在两个队列中通过 Harrell 一致性指数（C 指数）和校准图评估预测列线图。
共纳入 191 例患者，其中 135 例为主要队列，56 例为验证队列。性别、年龄、基线 NIHSS 评分、高同型半胱氨酸血症（HHcy）和多发病灶与中风后急性认知障碍独立相关，并纳入构建列线图。主要队列的列线图的曲线下面积（AUC）为 0.773，验证队列的 AUC 为 0.859。校准图表明列线图的预测值拟合良好。
基于性别、年龄、基线 NIHSS 评分、HHcy 和多发病灶的新列线图为 AIS 患者的认知障碍提供了准确全面的预测。经过进一步验证，它可能成为一种可靠的预测工具。
