摘要
卒中病程较长且受多种因素共同影响,深入探究不同干预措施对其病程和预后的作用,可为精准化卒中干预策略的制订提供重要依据。马尔可夫模型能够计算疾病在一定时期内的状态转移概率,模拟疾病的发展过程,并清晰比较各个病程阶段下不同干预措施的效果,助力卒中预后结局的精准预测与改善。基于此,本研究综述了马尔可夫模型的定义、原理、构建方法及其在卒中临床决策研究中的应用情况,以期为国内相关研究提供有益思路。
Stroke has a long course and is affected by multiple factors.In-depth exploration of the effects of different intervention measures on the disease course and prognosis can provide critical evidence for developing precision intervention strategies.The Markov model,by calculating the probabilities of state transitions in a disease over a certain period,can effectively simulate disease progression and clearly compare the effects of different intervention measures across various stages,thereby enhancing the precision in predicting stroke prognosis and improving its outcomes.Based on these advantages,this study reviews the definition,principles,and construction methods of Markov models and their applications in stroke clinical decision-making,aiming to provide valuable insights for related research in China.
作者
黄馨莹
柯嘉雯
陆作林
姜勇
邵瑞太
HUANG Xinying;KE Jiawen;LU Zuolin;JIANG Yong;SHAO Ruitai(School of Population Medicine and Public Health,Chinese Academy of Medical Sciences&Peking Union Medical College,Beijing 100730,China;China National Clinical Research Center for Neurological Diseases,Beijing Tiantan Hospital,Capital Medical University,Beijing 100070,China)
出处
《中国卒中杂志》
北大核心
2025年第8期1013-1021,共9页
Chinese Journal of Stroke
基金
卒中归因和精准干预研究(2021-RC330-004)
北京协和医学院慢性病群医学基地建设项目(WH10022022010)。
关键词
卒中
马尔可夫模型
临床决策
Stroke
Markov model
Clinical decision-making
