Fatigue in patients with inflammatory bowel disease is associated with distinct differences in immune parameters
Bibliographic record
Abstract
Background: Although it is well recognized that fatigue is an important problem in many of the quiescent inflammatory bowel disease (IBD) patients, it is unknown whether the immune status is different in fatigued versus non-fatigued patients. In this study, we contrasted various characteristics of the immune system in fatigued against non-fatigued patients with IBD in clinical remission. Patients and methods: Patients with IBD in clinical remission were phenotyped according to the Montreal classification, and the checklist individual strength-fatigue (CIS-fatigue) was used to assess fatigue (CIS-fatigue ≥ 35). Flow cytometry on peripheral blood samples was used to investigate differences in leukocyte subsets. The expression of various cytokines was determined in stimulated whole blood and serum samples using enzyme-linked immunosorbent assay. Differences between fatigued and non-fatigued patients with IBD were assessed. Results: In total, 55 patients were included in the fatigue group (FG) and 29 patients in the non-fatigue group (NFG). No differences in demographic and clinical characteristics were observed between the groups. Flow cytometry data showed a significantly lower percentage of monocytes ( p = 0.011) and a higher percentage of memory T-cells ( p = 0.005) and neutrophils ( p = 0.033) in the FG compared with the NFG. Whole blood stimulation showed increased TNF-α ( p = 0.022) and IFN-γ ( p = 0.047) in the FG. The median serum level was significantly higher for IL-12 ( p < 0.001) and IL-10 ( p = 0.005) and lower for IL-6 ( p = 0.002) in the FG compared with NFG. Conclusion: Significant differences in immune profile between fatigued and non-fatigued patients with IBD in clinical remission were found, which point out to a chronically active and Th1-skewed immune system in patients with fatigue. Whether these immune differences are directly involved in the fatigue complaints via immune-to-brain communication pathways remains to be determined. As such, further exploration of the underlying immune effects associated with fatigue is warranted to determine potential treatment options. Keywords: inflammatory bowel disease, fatigue, leukocyte subsets, cytokines
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".