Huang Zhi-Xin, Lu Haike, Lu Yi, Dai Yingyi, Lin Jianguo, Liu Zhenguo
NeuroMedical Center, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, 510317, Guangdong, China.
Interventional Vascular Surgery Department, Guangdong Second Provincial General Hospital, Guangzhou, Guangdong, China.
Sci Rep. 2025 Mar 17;15(1):9187. doi: 10.1038/s41598-025-93741-8.
Minor ischemic stroke (MIS) patients face significant risks of recurrent strokes, necessitating reliable predictive tools. This single-center retrospective study developed and validated a novel model for predicting 1-year stroke recurrence in MIS patients, defined as those with National Institutes of Health Stroke Scale scores < 4 within seven days of symptom onset. Among 218 patients (median age 64 years, 26.6% female), 32 (14.7%) experienced recurrent strokes within one year. Analysis of clinical and lifestyle variables identified physical activity, large artery stroke, admission NIHSS score, and smoking as significant predictors, forming the PLANS model. The model demonstrated superior predictive performance compared to the Essen model, with a higher C-index (0.780 vs. 0.556) and better calibration. Risk reclassification metrics showed significant improvements, with integrated discrimination improvement of 20.3%, continuous net reclassification improvement of 41.7%, and median risk score improvement of 18.5%. The PLANS model, incorporating both traditional and novel risk factors, provides a valuable tool for patient stratification and personalized secondary prevention strategies. External validation in diverse cohorts is warranted to confirm these promising results.
轻度缺血性卒中（MIS）患者面临着中风复发的重大风险，因此需要可靠的预测工具。这项单中心回顾性研究开发并验证了一种用于预测MIS患者1年中风复发的新模型，MIS患者定义为症状发作7天内美国国立卫生研究院卒中量表（NIHSS）评分<4的患者。在218例患者（中位年龄64岁，2）6.6%为女性）中，32例（14.7%）在1年内发生了中风复发。对临床和生活方式变量的分析确定了身体活动、大动脉卒中、入院时NIHSS评分和吸烟为显著预测因素，形成了PLANS模型。与Essen模型相比，该模型表现出更好的预测性能，C指数更高（0.780对0.556）且校准更好。风险重新分类指标显示出显著改善，综合判别改善为20.3%，连续净重新分类改善为41.7%，中位风险评分改善为18.5%。PLANS模型纳入了传统和新的风险因素，为患者分层和个性化二级预防策略提供了有价值的工具。有必要在不同队列中进行外部验证，以证实这些有前景的结果。
