Vascular Disease Is Associated With Differences in Brain Structure and Lower Cognitive Functioning in Inflammatory Bowel Disease: A Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Vascular disease and cognitive impairment have been increasingly documented in inflammatory bowel disease (IBD), and both have been individually correlated with changes in brain structure. This study aimed to determine if both macro- and microstructural brain changes are prevalent in IBD and whether alterations in brain structure mediate the relationship between vascular disease and cognitive functioning. METHODS: Eighty-four IBD participants underwent multimodal magnetic resonance imaging. Volumetric and mean diffusivity measures of the thalamus, hippocampus, normal-appearing white matter, and white matter lesions were converted to age- and sex-adjusted z scores. Vascular comorbidity was assessed using a modified Framingham Risk Score and cognition was assessed using a battery of neuropsychological tests. Test scores were standardized using local regression-based norms. We generated summary statistics for the magnetic resonance imaging metrics and cognitive tests, and these were examined using canonical correlation analysis and linear regression modeling. RESULTS: Greater vascular comorbidity was negatively correlated with thalamic, normal-appearing white matter, and white matter lesion volumes. Higher Framingham Risk Score were also correlated with lower processing speed, learning and memory, and verbal fluency. Increased vascular comorbidity was predictive of poorer cognitive functioning, and this effect was almost entirely mediated (94.76%) by differences in brain structure. CONCLUSIONS: Vascular comorbidity is associated with deleterious effects on brain structure and lower cognitive functioning in IBD. These findings suggest that proper identification and treatment of vascular disease is essential to the overall management of IBD, and that certain brain areas may serve as critical targets for predicting the response to therapeutic interventions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".