Psychiatric comorbidity increases mortality in immune-mediated inflammatory diseases
Bibliographic record
Abstract
OBJECTIVE: We determined the association between any common mental disorder (CMD: depression, anxiety disorder, bipolar disorder) and mortality and suicide in three immune-mediated inflammatory diseases (IMID), inflammatory bowel disease (IBD), multiple sclerosis (MS) and rheumatoid arthritis (RA), versus age-, sex- and geographically-matched controls. METHODS: Using administrative data, we identified 28,384 IMID cases (IBD: 8695; MS: 5496; RA: 14,503) and 141,672 matched controls. We determined annual rates of mortality, suicide and suicide attempts. We evaluated the association of any CMD with all-cause mortality and suicide using multivariable Cox regression models. RESULTS: In the IMID cohort, any CMD was associated with increased mortality. We observed a greater than additive interaction between depression and IMID status (attributable proportion 5.2%), but a less than additive interaction with anxiety (attributable proportion -13%). Findings were similar for MS and RA. In IBD, a less than additive interaction existed with depression and anxiety on mortality risk. The IMID cohort with any CMD had an increased suicide risk versus the matched cohort without CMD. CONCLUSION: CMD are associated with increased mortality and suicide risk in IMID. In MS and RA, the effects of depression on mortality risk are greater than associations of these IMID and depression alone.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".