Liu Hui-Lin, Ni Shi-Hao, Zhang Xiao-Jiao, Long Wen-Jie, Dong Xiao-Ming, Liu Zhi-Ying, Liao Hui-Li, Yang Zhong-Qi
State Key Laboratory of Traditional Chinese Medicine Syndrome, the First Affiliated Hospital of Guangzhou University of Chinese Medicine Guangzhou 510006, China.
State Key Laboratory of Traditional Chinese Medicine Syndrome, the First Affiliated Hospital of Guangzhou University of Chinese Medicine Guangzhou 510006, China Guangdong Provincial Hospital of Traditional Chinese Medicine Guangzhou 510407, China.
Zhongguo Zhong Yao Za Zhi. 2025 May;50(10):2865-2874. doi: 10.19540/j.cnki.cjcmm.20250212.502.
Based on latent structure model and association rule analysis, this study investigates the prescription patterns used by professor YANG Zhong-qi in treating hypertension with traditional Chinese medicine(TCM) and infers the associated TCM syndromes, providing a reference for clinical syndrome differentiation and treatment. The observation window spanned from January 8, 2013, to June 26, 2024, during which qualified herbal decoction prescriptions meeting efficacy criteria were extracted from the outpatient medical record system of the First Affiliated Hospital of Guangzhou University of Chinese Medicine and compiled into a standardized database. Statistical analysis of high-frequency herbs included frequency counts and herbal property-channel tropism analysis. Latent structure modeling and association rule analysis were performed using R 4.3.2 and Lantern 5.0 software to identify core herbal combinations and infer TCM syndrome patterns. A total of 2 436 TCM prescriptions were included in the study, involving 263 drugs with a cumulative frequency of 29 783. High-frequency herbs comprised Uncariae Ramulus cum Uncis, Poria, Glycyrrhizae Radix et Rhizoma, Puerariae Lobatae Radix, and Alismatis Rhizoma, predominantly categorized as deficiency-tonifying, heat-clearing, and blood-activating and stasis-resolving herbs. Latent structure analysis identified 18 latent variables, 74 latent classes, 5 comprehensive clustering models, and 15 core herbal combinations, suggesting that the core syndrome clusters include liver Yang hyperactivity pattern, Yin deficiency with Yang hyperactivity pattern, phlegm-stasis intermingling pattern, and liver-kidney insufficiency pattern. Association rule analysis revealed 22 robust association rules. RESULTS:: indicate that hypertension manifests as a deficiency-rooted excess manifestation, significantly associated with functional dysregulation of the liver, lung, spleen-stomach, heart, and kidney. Key pathogenic mechanisms involve liver Yang hyperactivity, phlegm-stasis interaction, and liver-kidney insufficiency. Therapeutic strategies should prioritize liver-calming, spleen-fortifying, and deficiency-tonifying principles, supplemented by dynamic regulation of Qi-blood and Yin-Yang balance according to syndrome evolution, alongside pathogen-eliminating methods such as phlegm-resolving and stasis-dispelling. Synergistic interventions like mind-tranquilizing therapies should be tailored to individual conditions.
基于潜在结构模型和关联规则分析，本研究探讨了杨忠奇教授运用中医药治疗高血压的用药规律，并推断相关中医证候，为临床辨证论治提供参考。观察窗口为2013年1月8日至2024年6月26日，在此期间，从广州中医药大学第一附属医院门诊病历系统中提取符合疗效标准的合格中药汤剂处方，并编制成标准化数据库。对高频药物进行统计分析，包括频数统计和药物性味归经分析。使用R 4.3.2和Lantern 5.0软件进行潜在结构建模和关联规则分析，以识别核心药物组合并推断中医证候模式。本研究共纳入2436份中药处方，涉及263味药物，累计频数为29783次。高频药物包括钩藤、茯苓、甘草、葛根、泽泻，主要分为补虚药、清热药、活血化瘀药。潜在结构分析确定了18个潜在变量、74个潜在类别、5个综合聚类模型和15个核心药物组合，提示核心证候聚类包括肝阳上亢证、阴虚阳亢证、痰瘀互结证、肝肾不足证。关联规则分析揭示了22条强关联规则。结果表明，高血压表现为本虚标实之象，与肝、肺、脾胃、心、肾的功能失调显著相关。关键病机为肝阳上亢、痰瘀互结、肝肾不足。治疗策略应注重平肝、健脾、补虚原则，根据证候演变动态调整气血阴阳平衡，并辅以化痰祛瘀等祛邪方法。应根据个体情况定制如安神疗法等协同干预措施。
