| 引用本文: |
张媛婷,胡宗仁,蔡虎志,陈新宇.基于“三态四浊”理论的高脂血症表征体系及其预警应用初探[J].湖南中医药大学学报,2023,43(10):1885-1889[点击复制] |
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| 基于“三态四浊”理论的高脂血症表征体系及其预警应用初探 |
| 张媛婷,胡宗仁,蔡虎志,陈新宇 |
| (湖南中医药大学第一中医临床学院, 湖南 长沙 410007;湖南医药学院康复医学与保健学院, 湖南 怀化 418000;湖南中医药大学第一附属医院, 湖南 长沙 410007) |
| 摘要: |
| 高脂血症是常见慢性疾病，进行疾病预警并提前干预是降低发病率的关键手段。本文旨在探索一种新的“治未病”研究范式，通过生物信息与机器学习的结合，系统理解高脂血症“治未病”的现代医学内涵。基于高脂血症“三态四浊”理论的预警体系，重点关注从“欲病态”到“已病态”人体体征、血液、尿液以及粪便的生物信息从“清”到“浊”的动态变化过程。通过高脂血症“欲病态”的多维动态数据，揭示高脂血症从“欲病态”到“已病态”的临界转变规律，通过数学模型量化“欲病态”以进行疾病风险预警，为理解高脂血症发病机制、预判高脂血症发病与进展、实现精准预防以及开发诊疗新技术提供新的研究思路。 |
| 关键词: 高脂血症 治未病 三态四浊 欲病态 已病态 机器学习 疾病预测 健康管理 |
| DOI：10.3969/j.issn.1674-070X.2023.10.021 |
| 投稿时间：2023-05-14 |
| 基金项目:国家自然科学基金项目（81704061，81173213）；全国名老中医药专家陈新宇传承工作室建设项目（国中医药人教函〔2022〕75号）；湖南省科学技术厅重点领域研发计划项目（2019SK2321）；湖南省发改委创新引导专项（湘发改投资2019-412号）；“四时调阳”治未病湖南省工程研究中心（湘发改高技〔2020〕1006号）。 |
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| Preliminary study on disease characterization system of hyperlipidemia and its early warning based on the theory of "three physical states and four turbid bio-indicators" |
| ZHANG Yuanting,HU Zongren,CAI Huzhi,CHEN Xinyu |
| (The First Clinical College of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan 410007, China;School of rehabilitation medicine and health care, Hunan Medical College, Huaihua, Hunan 418000, China;The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan 410007, China) |
| Abstract: |
| Hyperlipidemia is a common chronic disease, and its early warning and intervention are the key means to reduce the incidence rate. This paper aims to explore a new research paradigm of "preventing a disease before it arises", and systematically understand the modern medical connotation of "preventing the hyperlipidemia before it arises" through the combination of biological information and machine learning. The warning system of hyperlipidemia based on the theory of "three physical states and four turbid bio-indicators", focuses on the dynamic change process of the biological information of physical signs, blood, urine, and feces from "being clear" to "being turbid", during the transformation of the "pre-diseased state" into the "diseased state". Based on the multi-dimensional dynamic data of the "pre-diseased state" of hyperlipidemia, the critical transition law of hyperlipidemia from "pre-diseased state" to "diseased state" has been revealed, and the "pre-diseased state" has been quantified through mathematical model for the disease risk warning. It provides new research ideas for understanding the pathogenesis of hyperlipidemia, predicting its onset and progress, achieving precise prevention, and developing new diagnosis and treatment technologies for it. |
| Key words: hyperlipidemia "preventing a disease before it arises" "three physical states and four turbid bio-indicators" "pre-diseased state" "diseased state" machine learning disease prediction health management |
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