The status and correlation factors of fatigue in patients with ankylosing spondylitis (FACIT-F): a cross-sectional study based on the Chinese population

• Published in: BMC rheumatology Vol. 9; no. 1; pp. 34 - 9
• Main Authors: Sun, Tiantian, Yang, Kun, Chen, Yuening, Geng, Zhaoyang, Qu, Xinning, Yu, Qing, Liu, Hongxiao
• Format: Journal Article
• Language: English
• Published: London BioMed Central 20.03.2025; BMC
• Subjects: Ankylosing spondylitis; Disease activity; FACIT-F; Fatigue; Medicine; Medicine & Public Health; Psychological factors; Rheumatology; Psychological factors; Fatigue; Disease activity; FACIT-F; Ankylosing spondylitis
• ISSN: 2520-1026; 2520-1026
• DOI: 10.1186/s41927-025-00472-4

Objective To analyze the status and correlation factors of fatigue in patients with ankylosing spondylitis (AS), and provide a reference for improving the fatigue status of patients with AS. Method Using the AS-specific disease database of the Chinese Rheumatology Registration and Research Information Platform, patients with AS from 9 centers in China were selected as study subjects from March 2022 to September 2023. Functional Assessment of Chronic Illness Therapy Scale (FACIT-F) score, AS disease activity score-C-reactive protein (ASDAS-CRP), AS disease activity score-erythrocyte sedimentation rate (ASDAS-ESR), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Function Index (BASFI), Bath Ankylosing Spondylitis Measurement Index (BASMI), Patient Global Assessment (PGA) score, night pain score, Depression Anxiety Stress Scale (DASS-21) and AS International Community Health Index Assessment (ASAS-HI) were observed. Human leukocyte antigen B27 (HLA-B27), C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) of the patients were detected. The data were analyzed by Spearman correlation and multiple linear regression. Result A total of 338 patients with AS were included in this study. Spearman correlation analysis results of 338 AS patients with fatigue showed that age, disease course, ASDAS-CRP, ASDAS-ESR, BASDAI, PGA, BASFI, BASMI, ASAS-HI and so on were the main correlation factors of fatigue ( P  < 0.05); Multiple linear regression analysis showed that BASDAI, ASAS-HI, depression and so on were independent predictors of fatigue in AS patients ( P  < 0.05). Spearman correlation analysis of no or very mild fatigue group showed that age, ASDAS-CRP, ASDAS-ESR, BASDAI, BASFI, ASAS-HI and so on were the main correlation factors of fatigue ( P  < 0.05); Multiple linear regression analysis showed that age, BASDAI, ASAS-HI were the independent predictor of fatigue in AS patients ( P  < 0.05). Spearman correlation analysis in the mild and moderate fatigue group showed that ASDAS-CRP, BASDAI, PGA, BASFI, ASAS-HI and so on were the main factors influencing fatigue ( P  < 0.05); Multiple linear regression analysis showed that BASDAI, depression and stress were independent predictors of fatigue in AS patients ( P  < 0.05). Conclusion In this study, fatigue was obvious in 37.9% of AS patients, and patients’ fatigue levels were closely related to disease activity (ASDAS, BASDAI and PGA) and psychological factors (anxiety, depression and stress). At the same time, the higher the degree of fatigue, the more obvious the impact of disease activity and psychological factors on fatigue.