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疾病疲劳与亚健康疲劳患者舌脉数据的相关性分析。

Correlation Analysis of Data of Tongue and Pulse in Patients With Disease Fatigue and Sub-health Fatigue.

机构信息

Department of Basic Medical College, 66322Shanghai University of Traditional Chinese Medicine, Shanghai, China.

Shanghai Collaborative Innovation Center of Health Service in Traditional Chinese Medicine, 66322Shanghai University of Traditional Chinese Medicine, Shanghai, China.

出版信息

Inquiry. 2022 Jan-Dec;59:469580211060781. doi: 10.1177/00469580211060781.

DOI:10.1177/00469580211060781
PMID:35112891
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8819780/
Abstract

Fatigue is one of the most common subjective symptoms of abnormal health state, there is still no reliable and stable evaluation method to distinguish disease fatigue and non-disease fatigue. Studies have shown that tongue diagnosis and pulse diagnosis are the reflection of overall state of the body. This study aims to explore the distribution rules and correlation of data of tongue and pulse in population with disease fatigue and sub-health fatigue and provide a new method of clinical diagnosis of fatigue from the perspective of tongue diagnosis and pulse diagnosis. In this study, a total of 736 people were selected and divided into healthy controls (n = 250), sub-health fatigue group (n = 242), and disease fatigue group (n = 244). TFDA-1 tongue diagnosis instrument and PDA-1 pulse diagnosis instrument were used to collect tongue image and sphygmogram, simple correlation analysis and canonical correlation analysis were used to analyze the correlation of tongue and pulse data about the two groups of fatigue people. The study had shown that tongue and pulse data could provide a certain reference for the diagnosis of different types of fatigue, tongue and pulse data in disease fatigue and sub-health fatigue population had different distribution rules, and there was a simple correlation and canonical correlation in the disease fatigue population, the coefficient of canonical correlation was .649 (P <.05).

摘要

疲劳是异常健康状态中最常见的主观症状之一，但目前仍没有可靠且稳定的评估方法来区分疾病性疲劳和非疾病性疲劳。研究表明，舌诊和脉诊是机体整体状态的反映。本研究旨在探讨疾病性疲劳和亚健康性疲劳人群的舌诊和脉诊数据分布规律及其相关性，从舌诊和脉诊角度为疲劳的临床诊断提供新方法。本研究共选取 736 人，分为健康对照组（n = 250）、亚健康性疲劳组（n = 242）和疾病性疲劳组（n = 244）。使用 TFDA-1 舌诊仪和 PDA-1 脉诊仪采集舌象和脉象，采用简单相关分析和典型相关分析对两组疲劳人群的舌诊和脉诊数据的相关性进行分析。研究表明，舌诊和脉诊数据可为不同类型的疲劳诊断提供一定参考，疾病性疲劳和亚健康性疲劳人群的舌诊和脉诊数据分布规律不同，疾病性疲劳人群中存在简单相关和典型相关，典型相关系数为.649（P <.05）。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/cf72535dd0b8/10.1177_00469580211060781-fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/7973c3ef9ac7/10.1177_00469580211060781-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/8936c98d1fff/10.1177_00469580211060781-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/201f141e9205/10.1177_00469580211060781-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/4f740325de5d/10.1177_00469580211060781-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/ab744c633ab4/10.1177_00469580211060781-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/f8c2c9804261/10.1177_00469580211060781-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/14afd9af0273/10.1177_00469580211060781-fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/cf72535dd0b8/10.1177_00469580211060781-fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/7973c3ef9ac7/10.1177_00469580211060781-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/8936c98d1fff/10.1177_00469580211060781-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/201f141e9205/10.1177_00469580211060781-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/4f740325de5d/10.1177_00469580211060781-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/ab744c633ab4/10.1177_00469580211060781-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/f8c2c9804261/10.1177_00469580211060781-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/14afd9af0273/10.1177_00469580211060781-fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5ae/8819780/cf72535dd0b8/10.1177_00469580211060781-fig8.jpg

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本文引用的文献

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Complement Ther Med. 2021 Jan;56:102607. doi: 10.1016/j.ctim.2020.102607. Epub 2020 Nov 19.
2
Chronic fatigue and fibromyalgia symptoms are key components of deficit schizophrenia and are strongly associated with activated immune-inflammatory pathways.慢性疲劳和纤维肌痛症状是缺陷型精神分裂症的关键组成部分，与激活的免疫炎症途径密切相关。
Schizophr Res. 2020 Aug;222:342-353. doi: 10.1016/j.schres.2020.05.003. Epub 2020 May 26.
3
Chronic fatigue syndrome: progress and possibilities.
慢性疲劳综合征：进展与可能性。
Med J Aust. 2020 May;212(9):428-433. doi: 10.5694/mja2.50553. Epub 2020 Apr 5.
4
Effect of Baduanjin Qigong Exercise on Cancer-Related Fatigue in Patients with Colorectal Cancer Undergoing Chemotherapy: A Randomized Controlled Trial.八段锦气功锻炼对化疗结直肠癌患者癌因性疲乏的影响：一项随机对照试验。
Oncol Res Treat. 2019;42(9):431-439. doi: 10.1159/000501127. Epub 2019 Jul 2.
5
A Study of Machine-Learning Classifiers for Hypertension Based on Radial Pulse Wave.基于桡动脉脉搏波的高血压机器学习分类器研究
Biomed Res Int. 2018 Nov 11;2018:2964816. doi: 10.1155/2018/2964816. eCollection 2018.
6
Pulse Wave Cycle Features Analysis of Different Blood Pressure Grades in the Elderly.老年人不同血压等级的脉搏波周期特征分析
Evid Based Complement Alternat Med. 2018 May 22;2018:1976041. doi: 10.1155/2018/1976041. eCollection 2018.
7
An evaluation of different measures of color saturation.对不同颜色饱和度测量方法的评估。
Vision Res. 2018 Oct;151:117-134. doi: 10.1016/j.visres.2017.04.012. Epub 2017 Jun 9.
8
Engineering RGB color vision into Escherichia coli.将 RGB 彩色视觉工程融入大肠杆菌中。
Nat Chem Biol. 2017 Jul;13(7):706-708. doi: 10.1038/nchembio.2390. Epub 2017 May 22.
9
Fatigue.疲劳。
Acta Physiol (Oxf). 2016 Sep;218(1):3-4. doi: 10.1111/apha.12756.
10
Translating Fatigue to Human Performance.将疲劳转化为人类表现。
Med Sci Sports Exerc. 2016 Nov;48(11):2228-2238. doi: 10.1249/MSS.0000000000000929.