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基于模糊认知图的慢性心力衰竭中医核心病机量化研究OA

Quantitative study on core pathogenesis of chronic heart failure in traditional Chinese medicine based on fuzzy cognitive maps

中文摘要英文摘要

目的 针对慢性心力衰竭(CHF)中医病机复杂、演变规律难以量化分析的问题,引入模糊认知图(FCM)建模方法,构建多层次、可量化的病机拓扑网络,系统揭示本病的核心病机、分型差异及演变规律.方法 以《慢性心力衰竭中医诊疗指南(2022年)》为数据源,通过本体建模抽取79个实体节点(涵盖疾病、分型、病机、症状等),采用专家小组打分法结合文献证据构建FCM模型.利用Gephi软件进行网络可视化与多维分析.结果 ①模型量化显示,气虚为CHF始发病机,气虚与血瘀强关联[0.97(数据表示权重,下同)],二者共同构成CHF"气虚血瘀"的核心病机框架.②血瘀的中介中心度最高,是连接虚实病机的关键枢纽,血瘀与痰强相关揭示CHF病机"痰瘀同病"的特征.③分型差异分析表明,射血分数保留的心力衰竭(HFpEF)呈现"气虚(0.70)为基、血瘀(0.72)为枢"的病机特征,射血分数降低的心力衰竭(HFrEF)则呈现"血瘀(0.67)、水饮(0.56)标实亢进"的病机特征.④纽约心脏病协会(NYHA)心功能分级差异分析揭示了病机随疾病进展的演变链:Ⅰ级以气虚(0.64)为本,血瘀(0.73)为标;Ⅱ级气虚(0.78)、血瘀(0.77)加重,阴虚(0.28)略显;Ⅲ级为转折期,气虚(0.80)、血瘀(0.81)达到高峰,水饮(0.35)骤升;Ⅳ级水饮(0.58)壅盛与阳虚(0.30)凸显.病机整体呈现"气虚→血瘀→水饮→阳虚"的传变规律.结论 通过构建CHF中医病机的FCM拓扑网络,首次实现了"分型-分级-证素-证候-症状"多维关系的系统量化与可视化分析,明确了"气虚血瘀"作为CHF核心病机的网络枢纽地位,揭示了CHF分型、分级的病机差异及演变规律.该方法突破了传统病机研究在量化与可视化方面的局限,为中医病机研究提供了新的分析范式.

Objective To address the problems of complex pathogenesis and difficult quantitative analysis of transmission rules of chronic heart failure(CHF)in traditional Chinese medicine(TCM),this paper introduced the fuzzy cognitive map(FCM)modeling method to construct a multi-level,quantifiable pathogenesis topological network,and systematically reveal the core pathogenesis,pattern classification differences and transmission rules of the CHF.Methods Taking the Chinese Medicine Diagnosis and Treatment Guidelines for Chronic Heart Failure(2022)as the data source,79 entity nodes(covering diseases,classifications,pathogenesis,and symptoms)were extracted through ontology modeling,and the FCM model was constructed by combining the expert panel scoring method with literature evidence.Gephi software was used for network visualization and multi-dimensional analysis.Results ①Quantitative analysis of the model showed that qi deficiency was the initial pathogenesis of CHF,and strongly correlated with blood stasis(weight=0.97,the same applied below),which constituted the core framework of"qi deficiency and blood stasis"in CHF.② Blood stasis had the highest betweenness centrality and was the key pivot connecting deficient and excessive pathogenesis.The strong correlation between blood stasis and phlegm revealed the characteristic of"concomitant phlegm and blood stasis"in the CHF pathogenesis.③Analysis of pattern classification differences demonstrated that heart failure with preserved ejection fraction(HFpEF)presented the pathogenesis characteristics of"qi deficiency(0.70)as the foundation and blood stasis(0.72)as the pivot",while heart failure with reduced ejection fraction(HFrEF)presented the characteristics of"hyperactivity of excessive symptoms of blood stasis(0.67)and water retention(0.56)".④Analysis of differences in New York Heart Association(NYHA)functional classification revealed the transmission chain of pathogenesis with disease progression:Grade Ⅰ was characterized by qi deficiency(0.64)as the root cause and blood stasis(0.73)as the manifestation;Grade Ⅱ showed aggravated qi deficiency(0.78)and blood stasis(0.77)with mild yin deficiency(0.28);Grade Ⅲ was a turning point,with qi deficiency(0.80)and blood stasis(0.81)reaching a peak and a sudden rise in water retention(0.35);and Grade Ⅳ was marked by excessive water retention(0.58)and prominent yang deficiency(0.30).Overall,the pathogenesis presented the transmission rule of"qi deficiency → blood stasis → fluid retention → yang deficiency".Conclusions By constructing an FCM-based topological network for TCM pathogenesis in CHF,this paper for the first time achieved systematic quantification and visual analysis of the multidimensional relationships of"classification-grading-syndrome element-syndrome-symptom",clarified the network pivot status of"qi deficiency and blood stasis"as the core pathogenesis of CHF,and revealed the pathogenesis differences and transmission rules of CHF across different classifications and grades.This method breaks through the limitations of traditional pathogenesis research in quantification and visualization,and provides a new analytical paradigm for TCM pathogenesis research.

姬新珂;赵芸;张雪芹;李平;文天才

北京中医药大学第三附属医院心内科(北京 100029)中国中医科学院中医药数据中心(北京 100700)中国中医科学院中医药数据中心(北京 100700)北京中医药大学第三附属医院心内科(北京 100029)中国中医科学院中医药数据中心(北京 100700)

慢性心力衰竭模糊认知图人工智能知识图谱中医病机

chronic heart failurefuzzy cognitive mapartificial intelligenceknowledge graphtraditional Chinese medicine pathogenesis

《上海中医药杂志》 2026 (7)

1-9,9

国家自然科学基金项目(82374624)北京市自然科学基金面上项目(7232306)中国中医科学院中医药数据中心自主选择项目(ZZ1718-XRZ-110-SJ)中国中医科学院新入职科研人员启动资金专项(ZZ16-XRZ-098)

10.16305/j.1007-1334.2026.z20250917004

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