A quantile regression approach to explain the relationship of Fatigue and Cortisol, Cytokine among Koreans with Hepatitis B

Yeonsoo Jang, Jeong Hyun Kim, Hyangkyu Lee, Kyunghwa Lee, Sang Hoon Ahn

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Fatigue is a major symptom among patients with Hepatitis B virus (HBV). However, the physiological mechanisms regarding mediate fatigue and the relationships between fatigue, cortisol and cytokines are unclear in patients with HBV. The purpose of this study was to examine the relationships between perceived fatigue, cortisol, and cytokines in Korean patients with HBV. The mean score for overall fatigue was moderate. In linear regression analyses, TNF-α was only significant as a predictor of fatigue. In quantile regression analyses, the cortisol level was significant in the 70th, 80th, 90th quantiles in the cognitive/mood fatigue subdimension, which correspond to severe levels of fatigue. IL-6 levels were significant in 90th quantile in overall fatigue and in the cognitive/mood fatigue subdimension. Cortisol, IL-6, and TNF- α were related to perceived fatigue in patients with HBV, particularly in the cognitive/mood dimension. This suggests that the fatigue patterns of patients with HBV are related to their mental and mood states and physical responses, such as cortisol and cytokine levels, are correlated with the nature of the fatigue. In the clinic, interventions to manage fatigue in patients with HBV should be developed based on the characteristics of the fatigue.

Original languageEnglish
Article number16434
JournalScientific reports
Volume8
Issue number1
DOIs
Publication statusPublished - 2018 Dec 1

Bibliographical note

Funding Information:
Competing Interests: Dr. Yeonsoo Jang received the research support by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2011-0024717). The other authors declare no competing interests.

Publisher Copyright:
© 2018, The Author(s).

All Science Journal Classification (ASJC) codes

  • General

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