Marital status and age of systemic lupus erythematous diagnosis: the potential for differences related to sex and gender
Bibliographic record
Abstract
OBJECTIVES: Chronic rheumatic diseases can challenge social and family relationships. We compared marital status in patients with systemic lupus erythematous (SLE) with their general population counterparts, stratified by sex and age of SLE onset. METHODS: We performed a cross-sectional analysis of a cohort of 382 patients with SLE at our centre (349 females, 33 males). We determined how many were married or living common-law at the time of last study visit. Patients were then divided into: SLE diagnosis before 18, between 18 and 30, between 31 and 44 and after 45 years of age. We then compared marital status among male and female patients with SLE, to Quebec age-specific marital statistics. RESULTS: Of 382 patients with SLE, 202 (52.9%) were married or living common-law, which was 9% lower than general population rates (95% CI 2% to 16%). One-third of women with paediatric-onset SLE were married or living common-law, which was 28% lower than their general population counterparts (95% CI 6% to 46%). Half of women diagnosed between age 18 and 30 were married or living common law, which was 14% less than general population rates (95% CI 4% to 25%). We could not establish significant differences for women diagnosed after age 30, or for males, versus their general population counterparts. CONCLUSIONS: Women diagnosed with SLE before age 30 were less likely to be married/living common-law, versus general population rates. This was not apparent for those diagnosed later in life. We did not clearly establish this effect in males, possibly due to power issues (vs a true effect of sex/gender). Additional studies (eg, focus groups) could elucidate reasons for our findings.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".