Brain-Gut Interplay: Cognitive Performance and Biomarker Correlations in IBD Patients
Bibliographic record
Abstract
Background/Objectives: Inflammatory bowel diseases (IBD), including mainly ulcerative colitis (UC) and Crohn’s disease (CD), have been associated with cognitive and psychological changes, though the mechanisms remain unclear. Methods: This prospective case-control study aimed to evaluate cognitive performance and biomarkers (homocysteine, serum amyloid A, brain-derived neurotrophic factor, and S100B protein) in IBD patients. Results: A total of 90 individuals (34 UC, 21 CD, and 35 controls) were assessed using the Montreal Cognitive Assessment (MoCA), the Memory Impairment Index (MIS), and biomarker analysis. MoCA and MIS testing showed significant differences between UC, CD, and the controls, with lower scores observed in IBD groups (p = 0.003, p = 0.015). Regarding trail-making tests, digit symbol substitution tests, and forward and backward digit spans, no significant changes were observed. No functional deficits were observed in daily activities. Biomarker analysis revealed lower brain-derived neurotrophic factor and higher serum amyloid A levels in IBD patients, correlated to MOCA and MIS scores. There were no significant differences in psychological distress between IBD patients and the controls. Subtle cognitive declines were noted across all groups during the 1-year follow-up, without any statistical significance when groups were compared. Conclusions: In conclusion, IBD patients reported lower cognitive scores compared to the controls, while no differences in depression and anxiety scores were observed. Higher BDNF levels correlated with better cognitive functioning, while higher serum amyloid A correlated with lower cognitive functioning.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".