Depression increases the risk of inflammatory bowel disease, which may be mitigated by the use of antidepressants in the treatment of depression
Bibliographic record
Abstract
OBJECTIVE: Depression is associated with IBD, but the effect of antidepressants on IBD has been sparsely studied. We assessed the impact of depression and antidepressant therapies on the development of IBD. DESIGN: The Health Improvement Network (THIN) was used to identify a cohort of patients with new-onset depression from 1986 to 2012. THIN patients who did not meet the defining criteria for depression were part of the referent group. The outcome was incident Crohn's disease (CD) or ulcerative colitis (UC). Cox proportional hazards modelling was performed to evaluate the rate of Crohn's disease or UC development among patients with an exposure of depression after controlling for age, sex, socioeconomic status, comorbid conditions, smoking, anxiety and antidepressant use including atypical antidepressants, mirtazapine, monoamine oxidase inhibitors (MAOI), serotonin norepinephrine reuptake inhibitors (SNRI), selective serotonin reuptake inhibitors (SSRI), serotonin modulators; and tricyclic antidepressants (TCA). RESULTS: We identified 403 665 (7.05%) patients with incident depression. Individuals with depression had a significantly greater risk of developing CD (adjusted HR=2.11, 95% CI 1.65 to 2.70) and UC (adjusted HR=2.23, 95% CI 1.92 to 2.60) after controlling for demographic and clinical covariates. SSRI and TCA were protective against CD, whereas mirtazapine, SNRI, SSRI, serotonin modulators and TCA were protective for UC. CONCLUSION: Patients with a history of depression were more likely to be diagnosed with IBD. In contrast, antidepressant treatments were selectively protective for Crohn's disease and UC. These results may impact counselling and management of depression and IBD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".