The risk of deliberate self-harm following a diagnosis of rheumatoid arthritis or ankylosing spondylitis: A population-based cohort study
Bibliographic record
Abstract
OBJECTIVE: Rheumatoid arthritis (RA) and ankylosing spondylitis (AS) are associated with mental illness. The risk of serious mental illness, including deliberate self-harm (DSH), in these conditions is not well known. We aimed to determine if RA or AS independently increases the risk for DSH. METHODS: We conducted retrospective, population-based cohort studies using administrative health data for the province of Ontario, Canada between April 1, 2002 and March 31, 2014. Individuals with incident RA (N = 53,240) or AS (N = 13,964) were separately matched 1:4 by age, sex, and year with comparators without RA or AS. The outcome was a first DSH attempt identified using emergency department data. We estimated hazard ratios (HR) and 95% confidence intervals (95% CI) for risk of DSH in RA and AS versus comparators, adjusting for demographic, clinical and health service utilization variables. RESULTS: Subjects with AS were significantly more likely to self-harm (crude incidence rate [IR] of 0.68/1,000 person years [PY] versus 0.32/1,000 PY in comparators), with an adjusted HR of 1.59 (95% CI 1.15 to 2.21). DSH was increased for RA subjects (IR 0.35/1,000 PY) versus comparators (IR 0.24/1,000 PY) only before (HR 1.43, 95% CI 1.16 to 1.74), but not after covariate adjustment (HR 1.07, 95% CI 0.86 to 1.33). CONCLUSIONS: AS carries an increased risk for DSH but no such risk was observed in RA. Further evaluation of at-risk AS subjects is needed, including the longitudinal effects of disease and arthritis therapies on self-harm behaviour. This will inform whether specific risk-reduction strategies for DSH in inflammatory arthritis are needed.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".