Clinical data mining on network of symptom and index and correlation of tongue-pulse data in fatigue population

Abstract

Background: Fatigue is a kind of non-specific symptom, which occurs widely in sub-health and various diseases. It is closely related to people's physical and mental health. Due to the lack of objective diagnosis criteria, it is often neglected in clinical diagnosis, especially in the early disease stage. Many clinical practices and research have shown that tongue and pulse conditions reflect the body's overall state. Establishing an objective evaluation method for diagnosing disease fatigue and non-disease fatigue by combining clinical symptoms, indexes, and tongue & pulse data is of great significance for timely and effective clinical treatment.

Methods: In this study, 2632 physical examination populations were divided into healthy controls, sub-health fatigue group, and disease fatigue group. Complex network technology was used to screen out the core symptoms and Western medicine indexes of sub-health fatigue and disease fatigue populations. Pajek software was used to construct the core symptoms/indexes network and core symptoms-indexes combined network. Simultaneously, the canonical correlation analysis method was used to analyze the objective tongue & pulse data between the two groups of fatigue population and analyze the distribution of tongue & pulse data.

Results: Some similarities were found in the core symptoms of sub-health fatigue and disease fatigue population, but with different node importance. The node-importance difference indicated that the diagnostic contribution rate of the same symptom to the two groups was different. The canonical correlation coefficient of tongue & pulse data in the disease fatigue group was 0.42 (P < 0.05). On the contrast, correlation analysis of tongue & pulse in the sub-health fatigue group showed no statistical significance.

Conclusions: The complex network technology was suitable for the correlation analysis of symptoms and indexes in the fatigue population, and the tongue & pulse data had a certain diagnostic contribution to the classification of the fatigue population.

Name of the registry: Chinese Clinical Trial Registry

Trial registration number: ChiCTR-IOR-15006502; ChiCTR1900026008

Date of registration: Jun. 04th, 2015

URL of trial registry record: http://www.chictr.org.cn/showprojen.aspx?proj=11119;

http://www.chictr.org.cn/edit.aspx?pid=38828&htm=4 (This is a retrospective registration)