Wang Nan, Liu Hongbing, Tian Mengke, Liang Jing, Sun Wenxian, Zhang Luyang, Pei Lulu, Liu Kai, Sun Shilei, Wu Jun, Gao Yuan, Xu Yuming, Wang Yilong, Song Bo
Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Front Neurol. 2022 Feb 25;13:827279. doi: 10.3389/fneur.2022.827279. eCollection 2022.
Lipids are implicated in inflammatory responses affecting acute ischaemic stroke prognosis. Therefore, we aimed to develop a predictive model that considers neutrophils and high-density lipoprotein cholesterol to predict its prognosis. This prospective study enrolled patients with acute ischaemic stroke within 24 h of onset between January 2015 and December 2017. The main outcome was a modified Rankin Scale score ≥3 at the 90th day of follow-up. Patients were divided into training and testing sets. The training set was divided into four states according to the median of neutrophils and high-density lipoprotein cholesterol levels in all patients. Through binary logistic regression analysis, the relationship between factors and prognosis was determined. A nomogram based on the results was developed; its predictive value was evaluated through internal and external validations. Altogether, 1,090 patients were enrolled with 872 (80%) and 218 (20%) in the training and testing sets, respectively. In the training set, the major outcomes occurred in 24 (10.4%), 24 (11.6%), 37 (17.2%), and 49 (22.3%) in states 1-4, respectively ( = 0.002). Validation of calibration and decision curve analyses showed that the nomogram showed better performance. The internal and external testing set receiver operating characteristics verified the predictive value [area under the curve = 0.794 (0.753-0.834), < 0.001, and area under the curve = 0.973 (0.954-0.992), < 0.001, respectively]. A nomogram that includes neutrophils and high-density lipoprotein cholesterol can predict the prognosis of acute ischaemic stroke, thus providing us with an effective visualization tool.
脂质与影响急性缺血性中风预后的炎症反应有关。因此,我们旨在建立一个考虑中性粒细胞和高密度脂蛋白胆固醇的预测模型来预测其预后。这项前瞻性研究纳入了2015年1月至2017年12月发病24小时内的急性缺血性中风患者。主要结局是随访第90天时改良Rankin量表评分≥3分。患者被分为训练集和测试集。根据所有患者中性粒细胞和高密度脂蛋白胆固醇水平的中位数,将训练集分为四种状态。通过二元逻辑回归分析,确定因素与预后之间的关系。基于结果绘制了列线图;通过内部和外部验证评估其预测价值。总共纳入了1090例患者,训练集和测试集分别有872例(80%)和218例(20%)。在训练集中,1-4状态下主要结局分别发生在24例(10.4%)、24例(11.6%)、37例(17.2%)和49例(22.3%)(P = 0.002)。校准验证和决策曲线分析表明列线图表现更佳。内部和外部测试集的受试者工作特征验证了其预测价值[曲线下面积分别为0.794(0.753 - 0.834),P < 0.001,以及0.973(0.954 - 0.992),P < 0.001]。一个包含中性粒细胞和高密度脂蛋白胆固醇的列线图可以预测急性缺血性中风的预后,从而为我们提供一种有效的可视化工具。