Rising incidence of psychiatric disorders before diagnosis of immune-mediated inflammatory disease
Bibliographic record
Abstract
AIMS: After the diagnosis of immune-mediated inflammatory diseases (IMID) such as inflammatory bowel disease (IBD), multiple sclerosis (MS) and rheumatoid arthritis (RA), the incidence of psychiatric comorbidity is increased relative to the general population. We aimed to determine whether the incidence of psychiatric disorders is increased in the 5 years before the diagnosis of IMID as compared with the general population. METHODS: Using population-based administrative health data from the Canadian province of Manitoba, we identified all persons with incident IBD, MS and RA between 1989 and 2012, and cohorts from the general population matched 5 : 1 on year of birth, sex and region to each disease cohort. We identified members of these groups with at least 5 years of residency before and after the IMID diagnosis date. We applied validated algorithms for depression, anxiety disorders, bipolar disorder, schizophrenia, and any psychiatric disorder to determine the annual incidence of these conditions in the 5-year periods before and after the diagnosis year. RESULTS: We identified 12 141 incident cases of IMID (3766 IBD, 2190 MS, 6350 RA) and 65 424 matched individuals. As early as 5 years before diagnosis, the incidence of depression [incidence rate ratio (IRR) 1.54; 95% CI 1.30-1.84) and anxiety disorders (IRR 1.30; 95% CI 1.12-1.51) were elevated in the IMID cohort as compared with the matched cohort. Similar results were obtained for each of the IBD, MS and RA cohorts. The incidence of bipolar disorder was elevated beginning 3 years before IMID diagnosis (IRR 1.63; 95% CI 1.10-2.40). CONCLUSION: The incidence of psychiatric comorbidity is elevated in the IMID population as compared with a matched population as early as 5 years before diagnosis. Future studies should elucidate whether this reflects shared risk factors for psychiatric disorders and IMID, a shared final common inflammatory pathway or other aetiology.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".