Fatigue in Peritoneal Dialysis Patients and an Exploration of Contributing Factors: A Cross-Sectional Study

Chong Tian; Beibei Zhang; Wangqun Liang; Qing Yang; Qianqian Xiong; Qiman Jin; Siyun Xiang; Jing Zhao; Chenjiang Ying; Xuezhi Zuo

doi:10.1016/j.jpainsymman.2019.12.351

Fatigue in Peritoneal Dialysis Patients and an Exploration of Contributing Factors: A Cross-Sectional Study

J Pain Symptom Manage. 2020 May;59(5):1074-1081.e2. doi: 10.1016/j.jpainsymman.2019.12.351. Epub 2019 Dec 20.

Authors

Affiliations

¹ School of Nursing, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
² Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
³ Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
⁴ Department of Clinical Nutrition, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China. Electronic address: zuo1967@tjh.tjmu.edu.cn.

PMID: 31866487
DOI: 10.1016/j.jpainsymman.2019.12.351

Abstract

Context: Fatigue is a common and detrimental symptom in dialysis patients; however, our understanding of it and investigation of its contributing factors is still very limited, especially in peritoneal dialysis (PD) patients.

Objectives: To assess fatigue in PD patients and identify contributing factors.

Methods: One hundred eight PD patients in a comprehensive hospital in China were recruited. The fatigue severity of the participants was assessed using the Chalder Fatigue Scale 11. Demographic factors and results of physiological tests were collected. Quality of sleep, mental health, and social support were assessed with the Pittsburgh Sleep Quality Index, Symptom Checklist 90, and Social Support Rating Scale, respectively. Multiple linear regression models were conducted with candidate variables with a P-value of less than 0.1 on univariate analysis and variables that were clinically relevant to identify contributing factors for fatigue.

Results: The fatigue level in PD patients was significantly higher than the community population, and 78.7% of them were suffering from fatigue. The factors that were significantly associated with fatigue were quality of sleep, normalized protein nitrogen appearance, transferrin, alkaline phosphatase, and total cholesterol (adjusted R squared 0.86). Among them, quality of sleep, transferrin, alkaline phosphatase, and total cholesterol were significant contributors for physical fatigue, whereas the quality of sleep and normalized protein nitrogen appearance were contributing factors for mental fatigue.

Conclusion: Fatigue is a common symptom in PD patients, suggesting that increased awareness of this symptom is required. The identification of correlates by extensive exploration of multidimensional factors in this study may help practitioners to identify patients at higher risk and to develop a multidimensional and targeted intervention plan.

Keywords: Fatigue; mental health; peritoneal dialysis; quality of sleep; social support.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

China / epidemiology
Cross-Sectional Studies
Humans
Peritoneal Dialysis* / adverse effects
Quality of Life
Renal Dialysis*
Surveys and Questionnaires