Prevalence of Fatigue Among Inflammatory Bowel Disease Patients at a Tertiary Center in Saudi Arabia
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Abstract
Background: Fatigue is a common and distressing symptom in inflammatory bowel disease (IBD), yet it is rarely addressed in routine care. Most available evidence comes from Western and East Asian populations, with limited data from the Middle East. Objectives: To estimate the prevalence of fatigue in Saudi patients with IBD, using the Arabic-validated Brief Fatigue Inventory (BFI-A), and to examine associations with demographic, clinical, treatment, and laboratory factors. Methods: This cross-sectional study was conducted at King Abdulaziz University Hospital, Saudi Arabia, between March and December 2025. Patients aged ≥12 years with histologically confirmed IBD completed a structured telephone interview. Demographic characteristics, comorbidities, IBD control scores, Montreal classification, medication history, and laboratory results were collected. Patients experiencing severe flares, hospitalization, or another primary condition likely to explain fatigue were excluded. Fatigue severity was classified as none, mild, moderate, or severe. Associations were tested using chi-square and Kruskal–Wallis tests. Results: Among 286 patients (mean age, 30.8 ± 9.1 years; 57.7% male), 23.1% reported mild fatigue, 36.4% moderate fatigue, and 19.2% severe fatigue on the BFI-A. Fatigue severity was not associated with demographic factors, IBD type or phenotype, treatment exposure, or most laboratory parameters. Only serum iron (p = 0.011) and erythrocyte sedimentation rate (p = 0.023) differed across fatigue categories, without a clear dose–response pattern. Conclusions: Fatigue affects more than half of Saudi patients with IBD and is not explained by routine clinical or laboratory factors. Routine fatigue assessment and attention to biopsychosocial contributors may improve IBD care.
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This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/19438148.
Write a short summary of the research's main findings and how this work has moved the field forward.
Major issues
Including healthy controls and stratifying Crohn's disease patients by ASCA status would enhance the analytical depth by enabling both disease-level comparisons and immunological subgroup characterization
The cross-sectional design limits causal inference; a longitudinal cohort design would be required to establish temporal relationships and identify true causal risk factors for fatigue.
The study is subject to several potential biases, including selection bias due to its single tertiary-center setting, recall and response bias from self-reported telephone interviews, and …
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/19438148.
Write a short summary of the research's main findings and how this work has moved the field forward.
Major issues
Including healthy controls and stratifying Crohn's disease patients by ASCA status would enhance the analytical depth by enabling both disease-level comparisons and immunological subgroup characterization
The cross-sectional design limits causal inference; a longitudinal cohort design would be required to establish temporal relationships and identify true causal risk factors for fatigue.
The study is subject to several potential biases, including selection bias due to its single tertiary-center setting, recall and response bias from self-reported telephone interviews, and residual confounding from unmeasured variables such as psychological and sleep-related factors
Minor issues
Timing of laboratory measurements: Greater detail on the temporal proximity between laboratory values and fatigue assessment would improve interpretability.
Consistency in reporting: Minor inconsistencies in reporting sample sizes across tables and analyses should be standardized for clarity.
Competing interests
The author declares that they have no competing interests.
Use of Artificial Intelligence (AI)
The author declares that they used generative AI to come up with new ideas for their review.
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