Prevalence and factors associated with fatigue in patients with ulcerative colitis in China: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Fatigue is one of the most common symptoms reported by patients with ulcerative colitis (UC), while it has not been fully recognized and taken seriously in clinical practice. We aimed to investigate the prevalence of fatigue in patients with UC and identify the factors associated with fatigue and its severity in China. METHODS: A cross-sectional study was conducted in Affiliated Hospital of Nanjing University of Chinese Medicine from May 2020 to February 2021. Demographic and clinical characteristics were collected. Fatigue was evaluated with the Fatigue Severity Scale and the Multidimensional Fatigue Inventory. The Hospital Anxiety and Depression Scale, the Pittsburgh Sleep Index Scale and the Malnutrition Universal Screening Tool were respectively used to evaluate the anxiety, depression, sleep disturbance and nutritional risk of patients with UC. RESULTS: A total of 220 UC patients were enrolled in this study. The prevalence of fatigue in patients was 61.8%, of which in patients with disease activity was 68.2%, and in patients in remission was 40.0%. Univariate analysis indicated that the Montreal classification, disease activity, anemia, anxiety, depression, sleep disturbance and high nutritional risk were the factors associated with fatigue in Patients with UC. Multivariate logistic regression analysis showed that the Montreal classification (E3: E1, OR = 2.665, 95% CI = 1.134-6.216), disease activity (OR = 2.157, 95% CI = 1.055-4.410) and anxiety (OR = 2.867, 95% CI = 1.154-7.126) were related to an increased risk of fatigue. Disease activity (RC = 0.240, 95% CI = 0.193-0.674) and anxiety (RC = 0.181, 95% CI = 0.000-0.151) were associated with severity of fatigue. CONCLUSIONS: This study demonstrated that the prevalence of fatigue among UC patients in China. The Montreal classification, disease activity and anxiety are associated with an increased risk of fatigue.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".