Key symptoms selection for two major syndromes diagnosis of Chinese medicine in chronic hepatitis B
Key symptoms selection for two major syndromes diagnosis of Chinese medicine in chronic hepatitis B
复制标题
慢性乙型肝炎中医辨证两大证候重点选取
DOI：
10.1007/s11655-016-2253-3
复制
发表时间：
2017
影响因子：
2.9
通讯作者：
Hu Yi-yang
中科院分区：
文献类型：
--
作者：
Zhao Yu;Kang Hong;Peng Jing-hua;Xu Lin;Cao Zhi-wei;Hu Yi-yang
目的探讨慢性乙型肝炎（CHB）两大证候的关键症状，为中医决策提供临床依据。方法设计CM慢性乙型肝炎诊断标准量表，包括体格症状、舌象和脉象。收集695例湿热证（DH）或脾虚证（SD） CHB患者进行特征选择和建模，并在不同地点收集275例CHB患者进行验证。基于修正信息增益（IG）选择关键症状，并应用5个分类器辅助模型训练和验证。对分类精度和受试者工作特征曲线下面积进行了评价。结果(1)从原125个证候中筛选出13个DH证候关键证候和13个SD证候关键证候；(2)关键症状的诊断准确率与原总症状相近或更好；(3)验证阶段，关键症状能有效识别证候，尤其是DH证候，5个分类器的平均预测准确率可达0.864，平均AUC为0.772。结论选定的关键症状可作为单纯DH和SD证候的诊断要素直接应用于临床。(N0注册。: chictr - dcc - 10000759)
ObjectiveTo identify key symptoms of two major syndromes in chronic hepatitis B (CHB), which can be the clinical evidence for Chinese medicine (CM) doctors to make decisions.MethodsStandardization scales on diagnosis for CHB in CM were designed including physical symptoms, tongue and pulse appearance. The total of 695 CHB cases with dampness-heat (DH) syndrome or Pi (Spleen) deficiency (SD) syndrome were collected for feature selection and modeling, another 275 CHB patients were collected in different locations for validation. Key symptoms were selected based on modified information gain (IG), and 5 classifiers were applied to assist with models training and validation. Classification accuracy and area under receiver operating characteristic curves (AUC) were evaluated.Results(1) Thirteen DH syndrome key symptoms and 13 SD syndrome key symptoms were selected from original 125 symptoms; (2) The key symptoms could achieve similar or better diagnostic accuracy than the original total symptoms; (3) In the validation phase, the key symptoms could identify syndromes effectively, especially in DH syndrome, which average prediction accuracy on 5 classifiers could achieve 0.864 with the average AUC 0.772.ConclusionThe selected key symptoms could be simple DH and SD syndromes diagnostic elements applied in clinical directly. (Registration N0.: ChiCTR-DCC-10000759)