Park Soo-Hyun, Lee Ji Sung, Kim Tae Jung, Oh Mi Sun, Kim Ji-Woo, Lee Kyungbok, Yu Kyung-Ho, Lee Byung-Chul, Yoon Byung-Woo, Ko Sang-Bae
Department of Neurology, Soonchunhyang University Hospital Seoul, Seoul, Korea.
Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Transl Stroke Res. 2025 Jun 9. doi: 10.1007/s12975-025-01361-1.
Prognostication after acute ischemic stroke is crucial for long-term care plans. Although hyperacute management significantly affects outcomes, prognostic factors for patients receiving delayed care remain unknown. This study aimed to evaluate predictors and develop a method for estimating long-term mortality in patients with delayed hospital arrival 24 h after stroke symptom onset. Between January 2008 and December 2014, ischemic stroke patients who were admitted to the hospital more than 24 h from symptom onset were included in the linked dataset provided by the Clinical Research Center for Stroke, linked with claims data from the Health Insurance Review and Assessment Service. A nomogram was developed to estimate long-term mortality using clinical variables, with a predictive model assessed by Harrell's C-index. A total of 14,298 patients with acute ischemic stroke (66.5 years, mean age; 58.3%, male) were randomly assigned to training (n = 10,009) and validation (n = 4289) groups. Significant predictors of long-term mortality included older age, lower BMI, higher NIHSS score, stroke etiology, comorbidities (diabetes, coronary artery disease, dialysis, cancer), fasting blood sugar, use of antithrombotics/statins, and functional status at discharge. The Stroke Measures Analysis for Prognostic Testing - Mortality24 (SMART-M24) nomogram incorporated 17 predictors and achieved a C-index of 0.80 (95% CI, 0.79-0.81) in both groups. The SMART-M24 nomogram provides a prognostic tool for estimating long-term mortality in ischemic stroke patients with delayed hospital arrival 24 h after symptom onset. This model can assist clinical decision-making and long-term care planning for patients who have not undergone hyperacute treatment.
急性缺血性中风后的预后评估对于长期护理计划至关重要。尽管超急性期管理会显著影响预后，但接受延迟治疗的患者的预后因素仍不清楚。本研究旨在评估预测因素，并开发一种方法来估计中风症状发作后24小时延迟入院患者的长期死亡率。在2008年1月至2014年12月期间，症状发作后超过24小时入院的缺血性中风患者被纳入中风临床研究中心提供的关联数据集，并与健康保险审查和评估服务机构的理赔数据相关联。利用临床变量开发了一个列线图来估计长期死亡率，并通过Harrell C指数评估预测模型。共有14298例急性缺血性中风患者（平均年龄66.5岁；58.3%为男性）被随机分为训练组（n = 10009）和验证组（n = 4289）。长期死亡率的显著预测因素包括年龄较大、体重指数较低、美国国立卫生研究院卒中量表（NIHSS）评分较高、中风病因、合并症（糖尿病、冠状动脉疾病、透析、癌症）、空腹血糖、使用抗血栓药物/他汀类药物以及出院时的功能状态。用于预后测试的中风测量分析-死亡率24（SMART-M24）列线图纳入了17个预测因素，两组的C指数均为0.80（95%CI，0.79-0.81）。SMART-M24列线图为估计症状发作后24小时延迟入院的缺血性中风患者的长期死亡率提供了一种预后工具。该模型可以协助未接受超急性期治疗的患者进行临床决策和长期护理规划。
