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一种基于加权混合回归模型的ARDS中医疗效评价方法探讨
王海英1, 刘恩顺1, 何易2, 张鹤鸣2
1.天津中医药大学第二附属医院, 天津 300150;2.天津中医药大学, 天津 300193
摘要:
急性呼吸窘迫综合征(ARDS)是一种临床常见危重症,中医辨证治疗在参与该病的救治中显示了肯定的疗效,但因缺少合理的评价方法,其效果被部分掩盖和质疑,严重影响了中医药在该类难治性疾病救治中的应用。以患者个体化诊治信息的获取和利用为切入点,采用多个脏腑证候信息加权组合的方法提取辨证信息,结合对应的治疗及评价信息,架构符合中医个体化诊疗特征的从辨证论治到治疗效果的函数映射模型,提出一种以加权混合回归模型为数据基础的矩阵分析方法,用以判断中医辨治与临床疗效之间的因果关联,探讨建立一种中医辨证治疗ARDS的疗效评价方法。
关键词:  急性呼吸窘迫综合征  疗效评价方法  个体化诊治  矩阵分析  加权混合回归模型
DOI:10.11656/j.issn.1673-9043.2016.06.03
分类号:
基金项目:国家自然科学基金项目(81273999)。
An approach to TCM evaluate the efficacy of ARDS based on weighted mixed regression model
WANG Hai-ying1, LIU En-shun1, HE Yi2, ZHANG He-ming2
1.Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300150, China;2.Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China
Abstract:
Acute respiratory distress syndrome(ARDS) is a common clinical critical disease,of which the TCM treatment showed a positive effect in the treatment.However,the lack of reasonable evaluation method leas to the masked and questioned effect,which is seriously affecting the application of TCM in the treatment of refractory disease.This efficacy evaluation of TCM syndrome differentiation and treatment of ARDS tries to access to and use of individualized diagnosis and treatment information as a starting point,by extracting differentiation of syndromes of information with Zang and Fu information weighted combination method,combined with the treatment and evaluation of the corresponding information architecture,in order to architecture function mapping model meeting the individual diagnosis and treatment of Chinese medicine characteristics which contains treatment and therapeutic effect of syndrome differentiation.It proposed an analysis method based on weighted mixed regression model for data base matrix for the sake of judging the causal relation between TCM syndrome differentiation and clinical efficacy.
Key words:  acute respiratory distress syndrome  evaluation method of curative effect  individualized diagnosis and treatment  matrix analysis  weighted mixed regression model
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