中国医学创新2025，Vol.22Issue(6)：179-184,6.DOI:10.3969/j.issn.1674-4985.2025.06.041
脑卒中患者机械通气撤机影响因素的研究进展
Progress in the Study of Factors Affecting Withdrawal of Mechanical Ventilation in Stroke Patients
摘要
Abstract
Stroke is a serious cerebrovascular disease with high morbidity and mortality,which often leads to patients relying on mechanical ventilation.Withdrawal is a key link in mechanical ventilation management of stroke patients,and its success directly affects the prognosis of patients and the allocation of medical resources.This paper reviews the factors affecting the success of the withdrawal of stroke patients and the current research status of the withdrawal prediction model.It is found that programmed withdrawal,nurse-led withdrawal,stroke type,location,scope,ultrasonic assessment,diaphragm movement index,and early pulmonary rehabilitation training have significant effects on the success of withdrawal.At the same time,machine learning and artificial intelligence technologies show potential in building predictive models for downtime,but further construction and validation are needed.This paper also discusses the definition of successful withdrawal,and emphasizes the importance of unifying successful withdrawal criteria.Future studies need to expand the sample size,conduct multi-center clinical trials,explore individualized withdrawal strategies,and optimize withdrawal management using machine learning algorithms.关键词
脑卒中/机械通气/撤机/预测模型/机器学习Key words
Stroke/Mechanical ventilation/Withdrawal/Predictive modeling/Machine learning引用本文复制引用
刘美颀,张雪辉,李媛青,刘安昊,颜冉冉,吴冬梅..脑卒中患者机械通气撤机影响因素的研究进展[J].中国医学创新,2025,22(6):179-184,6.基金项目
济宁医学院2018年度教师科研扶持基金(JYFC2018KJ033) （JYFC2018KJ033）
