急性缺血性脑卒中患者早期神经功能恶化风险预测模型的研究进展

doi:10.3761/j.issn.2096-7446.2025.09.021

Abstract

Abstract:

Early neurological deterioration is the manifestation of the progression of acute ischemic stroke. There are many risk factors，which seriously affect the prognosis of patients. In this paper，the research reviewed the progress of risk prediction models for early neurological deterioration after non reperfusion therapy and reperfusion therapy in patients with acute ischemic stroke，summarized the aspects of model construction methods，basic conditions，predictive performance and predictive factors，so as to provide references for the construction and application of risk prediction models for early neurological deterioration in patients with acute ischemic stroke.

Key words: Ischemic Stroke, Early Neurological Deterioration, Risk, Prediction Model, Review Literature as Topic

CHEN Yanqin, FAN Lijun, ZHANG Menglian, ZHANG Wan, LI Caiyue, ZHAO Hua. Research progress on risk prediction models for early neurological deterioration in patients with acute ischemic stroke[J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(9): 1144-1148.

References 35

[1]	《中国脑卒中防治报告》编写组, 王陇德. 《中国脑卒中防治报告2021》概要[J]. 中国脑血管病杂志, 2023, 20(11):783-792,封3.
	China Stroke Prevention and Treatment Writing Group, Wang LD. Brief report on stroke prevention and treatment in China,2021[J]. Chin J Cerebrovasc Dis, 2023, 20(11):783-792,cover 3.
[2]	Irvine HJ, Battey TW, Ostwaldt AC, et al. Early neurological stability predicts adverse outcome after acute ischemic stroke[J]. Int J Stroke, 2016, 11(8):882-889. doi: 10.1177/1747493016654484 pmid: 27334760
[3]	Tian T, Wang LJ, Xu JL, et al. Prediction of early neurological deterioration in acute ischemic stroke patients treated with intravenous thrombolysis[J]. J Cereb Blood Flow Metab, 2023, 43(12):2049-2059.
[4]	Seners P, Ben Hassen W, Lapergue B, et al. Prediction of early neurological deterioration in individuals with minor stroke and large vessel occlusion intended for intravenous thrombolysis alone[J]. JAMA Neurol, 2021, 78(3):321-328. doi: 10.1001/jamaneurol.2020.4557 pmid: 33427887
[5]	Kwan J, Hand P. Early neurological deterioration in acute stroke:clinical characteristics and impact on outcome[J]. QJM, 2006, 99(9):625-633.
[6]	Grant SW, Collins GS, Nashef SAM. Statistical Primer:develop-ing and validating a risk prediction model[J]. Eur J Cardiotho-rac Surg, 2018, 54(2):203-208.
[7]	Yamamoto H, Bogousslavsky J, van Melle G. Different predictors of neurological worsening in different causes of stroke[J]. Arch Neurol, 1998, 55(4):481-486.
[8]	Birschel P, Ellul J, Barer D. Progressing stroke:towards an in-ternationally agreed definition[J]. Cerebrovasc Dis, 2004, 17(2/3):242-252.
[9]	Siegler JE, Boehme AK, Kumar AD, et al. What change in the national institutes of health stroke scale should define neuro-logic deterioration in acute ischemic stroke?[J]. J Stroke Cere-brovasc Dis, 2013, 22(5):675-682.
[10]	Miyamoto N, Tanaka Y, Ueno Y, et al. Demographic,clinical,and radiologic predictors of neurologic deterioration in patients with acute ischemic stroke[J]. J Stroke Cerebrovasc Dis, 2013, 22(3):205-210.
[11]	Seners P, Turc G, Oppenheim C, et al. Incidence,causes and pre-dictors of neurological deterioration occurring within 24 h following acute ischaemic stroke:a systematic review with pathophysiological implications[J]. J Neurol Neurosurg Psy-chiatry, 2015, 86(1):87-94.
[12]	Chung JW, Kim N, Kang J, et al. Blood pressure variability and the development of early neurological deterioration foll-owing acute ischemic stroke[J]. J Hypertens, 2015, 33(10):2099-2106.
[13]	Stone JA, Willey JZ, Keyrouz S, et al. Therapies for hemorr-hagic transformation in acute ischemic stroke[J]. Curr Treat Op-tions Neurol, 2017, 19(1):1.
[14]	Lee SJ, Hong JM, Lee SE, et al. Association of fibrinogen level with early neurological deterioration among acute ischemic stroke patients with diabetes[J]. BMC Neurol, 2017, 17(1):101.
[15]	梁玉婵, 韩小妍, 李素娟, 等. 非再灌注的轻型卒中早期神经功能恶化预测[J]. 中风与神经疾病杂志, 2022, 39(8):713-718.
	Liang YC, Han XY, Li SJ, et al. Predictive model for early neurological deterioration in minor ischemic stroke without reperfusion therapy[J]. J Apoplexy Nerv Dis, 2022, 39(8):713-718.
[16]	毛永佳, 罗鹏, 毛诗贤, 等. 急性缺血性脑卒中早期神经功能恶化预测模型构建及评价[J]. 现代预防医学, 2024, 51(1):166-172.
	Mao YJ, Luo P, Mao SX, et al. Construction and evaluation of a model for predicting the deterioration of neurological function in the early stage of acute ischemic stroke[J]. Mod Prev Med, 2024, 51(1):166-172.
[17]	肖静怡, 谢小华, 潘璐, 等. 急性缺血性脑卒中早期神经功能恶化风险预测模型的构建[J]. 护理研究, 2020, 34(19):3408-3412.
	Xiao JY, Xie XH, Pan L, et al. Development of risk prediction model for early neurological deterioration in acute ischemic stroke patients[J]. Chin Nurs Res, 2020, 34(19):3408-3412.
[18]	林斯革, 欧小凡. 急性缺血性脑卒中患者早期神经功能恶化影响因素分析及预测模型建立[J]. 解放军预防医学杂志, 2020, 38(10):129-132.
	Lin SG, Ou XF. Analysis of influencing factors of early neu-rological deterioration in patients with acute ischemic stroke and establishment of a predictive model[J]. J Prev Med Chin PLA, 2020, 38(10):129-132.
[19]	肖静怡, 谢小华, 王亚萍, 等. 基于IScore评分的早期神经功能恶化预测模型的构建与评价[J]. 护理学杂志, 2020, 35(17):32-35.
	Xiao JY, Xie XH, Wang YP, et al. Development and evaluation of IScore-based prediction model for early neurological deterioration[J]. J Nurs Sci, 2020, 35(17):32-35.
[20]	姚富远. 非溶栓急性缺血性卒中患者早期神经功能恶化的危险因素及预测模型研究[D]. 广州: 汕头大学医学院, 2023.
	Yao FY. Risk factors and predictive model research for early neurological deterioration in non-thrombolytic acute ischemic stroke patients[D]. Guangzhou: Shantou University Medical Col-lege, 2023.
[21]	汪云云. 急性缺血性脑卒中早期神经功能恶化影响因素与预警模型构建[D]. 合肥: 安徽医科大学, 2019.
	Wang YY. Influencing factors and early warning model con-struction for early neurological deterioration in acute ischemic stroke[D]. Hefei: Anhui Medical University, 2019.
[22]	Gong P, Zhang X, Gong Y, et al. A novel nomogram to predict early neurological deterioration in patients with acute is-chaemic stroke[J]. Eur J Neurol, 2020, 27(10):1996-2005.
[23]	Bugnicourt JM, Roussel B, Garcia PY, et al. Aspirin non-res-ponder status and early neurological deterioration:a prospe-ctive study[J]. Clin Neurol Neurosurg, 2011, 113(3):196-201.
[24]	中华护理学会内科专业委员会, 首都医科大学宣武医院. 急性缺血性脑卒中静脉溶栓护理指南[J]. 中华护理杂志, 2023, 58(1):10-15. doi: 10.3761/j.issn.0254-1769.2023.01.001
	Internal Medicine Committee of Chinese Nursing Association,Xuanwu Hospital of Capital Medical University. Guidelines for nursing care of intravenous thrombolysis in acute ischemic stroke[J]. Chin J Nurs, 2023, 58(1):10-15. doi: 10.3761/j.issn.0254-1769.2023.01.001
[25]	Zhou J, Gao Y, Ma QL. Safety and efficacy of tirofiban in acute ischemic stroke patients not receiving endovascular treat-ment:a systematic review and meta-analysis[J]. Eur Rev Med Pharmacol Sci, 2020, 24(3):1492-1503.
[26]	袁长红, 吴晓宇, 陈长春, 等. 急性脑梗死静脉溶栓后早期神经功能恶化的危险因素及预测模型分析[J]. 临床内科杂志, 2021, 38(6):396-398.
	Yuan CH, Wu XY, Chen CC, et al. Risk factors and predictive model analysis of early neurological deterioration after intra-venous thrombolysis in acute cerebral infarction[J]. J Clin Intern Med, 2021, 38(6):396-398.
[27]	李彬. 急性脑梗死阿替普酶溶栓后早期神经功能恶化预测模型的构建与验证[J]. 安徽医药, 2022, 26(8):1627-1632.
	Li B. Construction and verification of early neurological dete-rioration prediction model after alteplase thrombolysis in cerebral infarction[J]. Anhui Med Pharm J, 2022, 26(8):1627-1632.
[28]	边丽, 张秀梅, 李妍, 等. 急性脑梗塞患者溶栓后END发生风险预测模型的构建及急救优化方案的预防效果[J]. 中国实验诊断学, 2023, 27(6):631-637.
	Bian L, Zhang XM, Li Y, et al. Construction of risk prediction model of END after thrombolysis in patients with acute cerebral infarction prevention effect of first aid optimization scheme[J]. Chin J Lab Diagn, 2023, 27(6):631-637.
[29]	胡岩芳, 赵杨, 李喜朋. 高龄轻型脑卒中患者溶栓治疗后发生早期神经功能恶化的危险因素及列线图风险预测模型[J]. 广西医学, 2021, 43(9):1069-1073.
	Hu YF, Zhao Y, Li XP. Occurrence of early neurological deterioration after thrombolysis therapy in elderly patients with mild stroke:risk factors and nomogram model of risk prediction[J]. Guangxi Med J, 2021, 43(9):1069-1073.
[30]	Yang H, Lv Z, Wang WX, et al. Machine learning models for predicting early neurological deterioration and risk classi-fication of acute ischemic stroke[J]. Clin Appl Thromb Hemost, 2023, 29:10760296231221738.
[31]	Wang M, Liu YL. Construction of a prediction model for risk of early neurological deterioration following intravenous throm-bolysis in patients with acute ischemic stroke[J]. Technol Health Care, 31(6):2213-2223.
[32]	吕喆, 杨欢, 王耀辉, 等. 基于机器学习的急性缺血性脑卒中静脉溶栓后早期神经功能恶化预测模型的建立与评价[J]. 中华危重病急救医学, 2023, 35(9):945-950.
	Lü Z, Yang H, Wang YH, et al. Establishment and evaluation of a predictive model for early neurological deterioration after intravenous thrombolysis in acute ischemic stroke based on machine learning[J]. Chin Crit Care Med, 2023, 35(9):945-950.
[33]	徐守权, 唐国文, 黄舞标, 等. BP神经网络、随机森林和决策树预测急性脑梗死患者静脉溶栓后发生早期神经功能恶化的效能比较[J]. 实用心脑肺血管病杂志, 2023, 31(2):16-21.
	Xu SQ, Tang GW, Huang WB, et al. Comparison of the efficacy of BP neural network,random forest and decision tree in predicting early neurological deterioration after intra-venous thrombolysis in patients with acute cerebral infarction[J]. Pract J Card Cereb Pneumal Vasc Dis, 2023, 31(2):16-21.
[34]	刘艳平, 康玲伶, 崔会, 等. 缺血性脑卒中患者静脉溶栓术后早期神经功能恶化危险因素的Meta分析[J]. 河北医学, 2022, 28(12):2100-2104.
	Liu YP, Kang LL, Cui H, et al. Risk factors of early neuro-logical deterioration of patients with ischemic stroke under-going intravenous thrombolysis:a meta analysis[J]. Hebei Med, 2022, 28(12):2100-2104.
[35]	Yang TT, Hu YX, Pan XD, et al. Interpretable machine learning model predicting early neurological deterioration in ischemic stroke patients treated with mechanical thrombectomy:a retro-spective study[J]. Brain Sci, 2023, 13(4):557.

Research progress on risk prediction models for early neurological deterioration in patients with acute ischemic stroke

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References 35

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	YE Hongmin, GAN Xiuni, GAO Yan, ZHANG Huan, ZHOU Wen, LI Dongxue. Development and validation of a risk prediction model for venous thromboembolism in patients with intracerebral hemorrhage [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(9): 1042-1049.
[2]	ABUDU·Zulubiya , LI Ting, SUN Libing, CHEN Huijuan. Development and validation of a predictive model for deep vein thrombosis in patients with multiple trauma [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(9): 1067-1073.
[3]	WANG Yuan, WU Huiling, SHAO Lewen. Research progress on health-related quality of life and assessment tools for pregnant women with heart disease [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(9): 1149-1152.
[4]	WANG Yijia, PAN Aihong, LIU Rui, CHEN Qian, WANG Chengchen. Risk factors for post-traumatic stress disorders in family members of intensive care unit patients：a meta-analysis [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(8): 938-944.
[5]	MA Jiahui, LIN Hongjing, ZHANG Xueli, Qin Zeyu, JIANG Nan. Application progress and challenges of intelligent technology in rehabilitation nursing for critically ill patients [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(8): 953-956.
[6]	CHEN Ying, TANG Jiaying, GUO Zhiting, FENG Xiuqin. Reliability and validity testing of the Chinese version of Combined Outcome Measure for Risk Communication and Treatment Decision-Making Effectiveness in family members of ICU patients [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(8): 975-981.
[7]	SHENG Xiaoxuan, HUANG Sufang. Research progress on the influencing factors and interventions for return to work among patients with aortic dissection [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(6): 765-768.
[8]	ZHANG Jian, WANG Xiaoping, SHI Xusheng, XUE Xue, GAI Yubiao, GAO Silong, Guo Xiaojing, WEI Lili. Construction and validation of a risk assessment tool for acute skin failure in ICU patients [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(5): 517-523.
[9]	HONG Liuyu, CHEN Xiangping, LAO Yuewen, CHEN Qianqian, GONG Xiaoyan. Research progress on influencing factors and intervention strategies of pediatric chronic critical illness [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(5): 566-569.
[10]	ZHOU Feifei, GAO Chunhua, CHU Junqing, LIN Yan, WANG Xiaohong, QIAO Wenbo, REN Yayu. A review on mechanical ventilation withdrawal nursing for obese patients in ICU [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(5): 636-640.
[11]	HUANG Hui, JI Chaona, CHEN Lichan, CHEN Yanhong, CHEN Xisui. Development and validation of a risk prediction model of central venous catheter-associated skin injury in adult patients in the intensive care unit [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(4): 389-395.
[12]	SONG Yunlian, YAN Yan, SHAO Rongya, DING Weiyan. Analysis of the status and risk factors of unplanned return to ICU in patients with acute pancreatitis [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(4): 409-413.
[13]	HUANG Yufeng, DONG Lixia, ZHANG Lei, WANG Hui. Improvement of the nursing process for thrombolysis patients with acute ischemic stroke in Inner Mongolia and effect evaluation [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(3): 345-350.
[14]	ZHU Xiaojuan, YU Yang, WANG Cong, YIN Junlian, ZHEN Yushan, WANG Desheng, BAI Huihua. Summary of best evidence for management of blood pressure after mechanical embolectomy in patients with acute ischemic stroke [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(3): 365-371.
[15]	SU Yichao, HU Xiaoli, LI Qiufang. Research progress and prospect of intestinal microecological adjustment strategies in early life of premature Infants [J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(3): 372-375.