Understanding Predictors of Fatigue Over Time in Persons With Inflammatory Bowel Disease: The Importance of Depressive and Anxiety Symptoms
Bibliographic record
Abstract
INTRODUCTION: Fatigue is a complex and frequent symptom in persons with inflammatory bowel disease (IBD), with detrimental impact. We aimed to determine predictors of fatigue over time. METHODS: Two hundred forty-seven adults with IBD participated in a prospective study conducted in Manitoba, Canada, providing data at baseline and annually for 3 years. Participants reported fatigue impact (Daily Fatigue Impact Scale [DFIS]), depression and anxiety symptoms (Hospital Anxiety and Depression Scale [HADS]), and pain (Pain Effects Scale [PES]). Physician-diagnosed comorbidities, IBD characteristics, and physical and cognitive functioning were also assessed. We tested factors associated with fatigue using multivariable generalized linear models that estimated within-person and between-person effects. RESULTS: Most participants were women (63.2%), White (85.4%), and had Crohn's disease (62%). At baseline, 27.9% reported moderate-severe fatigue impact, 16.7% had clinically elevated anxiety (HADS-A ≥11), and 6.5% had clinically elevated depression (HADS-D ≥11). Overall fatigue burden was stable over time, although approximately half the participants showed improved or worsening fatigue impact between annual visits during the study. On multivariable analysis, participants with a one-point higher HADS-D score had, on average, a 0.63-point higher DFIS score, whereas participants with a one-point higher PES score had a 0.78-point higher DFIS score. Within individuals, a one-point increase in HADS-D scores was associated with 0.61-point higher DFIS scores, in HADS-A scores with 0.23-point higher DFIS scores, and in PES scores with 0.38-point higher DFIS scores. No other variables predicted fatigue. DISCUSSION: Anxiety, depression, and pain predicted fatigue impact over time in IBD, suggesting that targeting psychological factors and pain for intervention may lessen fatigue burden.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".