Shen Lvjie, Jin Bintao, Jiang Cao, Yu Jianqiang, Li Shuxing, Wang Yunhui
Emergency Department, Deqing People's Hospital, Deqing, Zhejiang Province, China.
Department of Neurology, Deqing People's Hospital, Deqing, Zhejiang Province, China.
Medicine (Baltimore). 2025 May 23;104(21):e42495. doi: 10.1097/MD.0000000000042495.
Symptomatic intracranial hemorrhage (SICH) is a severe post-endovascular treatment (EVT) complication of acute ischemic stroke, leading to high morbidity, mortality, and neurological deficits. However, despite these risk factors, there is currently no clinically accepted predictive model to predict SICH risk in EVT patients. This study aimed to identify independent perioperative risk factors for SICH and to provide a new nomogram-based predictive model for large vessel occlusion patients. This study retrospectively examined 127 acute ischemic stroke patients receiving EVT from the First Affiliated Hospital of Wenzhou Medical University. Inclusion criteria included the National Institutes of Health Stroke Scale (NIHSS), Alberta Stroke Program Early CT Score (ASPECTS), and American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology (ASITN/SIR) collateral scores. Using these predictors, a logistic regression model was used to generate the NIHSS/ASPECTS/ASITN (NAA) nomogram. The predictive ability was measured with the area under the receiver operating characteristic curve and calibration plots. Our data demonstrated that SICH patients had significantly higher baseline NIHSS scores (median: 22.38 vs 15.03; P < .001), ASPECTS (median: 5.89 vs 7.69; P < .001), and ASITN/SIR scores (median: 1.62 vs 2.69; P < .001). The NAA nomogram exhibited an area under the receiver operating characteristic curve value of 0.845 (95% confidence interval: 0.763-0.928), which is superior to the predictive performance. Calibration plots were robust in predicting and observing values. The NAA nomogram is a robust predictor of SICH after EVT that is more accurate than any scoring system. More external validation is needed to make it generalizable to diverse clinical settings.
症状性颅内出血（SICH）是急性缺血性卒中血管内治疗（EVT）后一种严重的并发症，会导致高发病率、死亡率和神经功能缺损。然而，尽管存在这些风险因素，但目前尚无临床上可接受的预测模型来预测EVT患者发生SICH的风险。本研究旨在确定SICH的围手术期独立危险因素，并为大血管闭塞患者提供一种新的基于列线图的预测模型。本研究回顾性分析了温州医科大学附属第一医院127例接受EVT治疗的急性缺血性卒中患者。纳入标准包括美国国立卫生研究院卒中量表（NIHSS）、阿尔伯塔卒中项目早期CT评分（ASPECTS）以及美国介入和治疗神经放射学会/介入放射学会（ASITN/SIR）侧支循环评分。利用这些预测指标，采用逻辑回归模型生成NIHSS/ASPECTS/ASITN（NAA）列线图。通过受试者操作特征曲线下面积和校准图来衡量预测能力。我们的数据表明，SICH患者的基线NIHSS评分显著更高（中位数：22.38对15.03；P < .001）、ASPECTS评分（中位数：5.89对7.69；P < .001）以及ASITN/SIR评分（中位数：1.62对2.69；P < .001）。NAA列线图的受试者操作特征曲线下面积值为0.845（95%置信区间：0.763 - 0.928），其预测性能更优。校准图在预测值和观察值方面表现稳健。NAA列线图是EVT后SICH的可靠预测指标，比任何评分系统都更准确。需要更多的外部验证，以便将其推广到不同的临床环境。
