A Population-level Analysis of the Differing Effects of Rheumatoid Arthritis and Spondyloarthritis on Peripartum Outcomes
Bibliographic record
Abstract
OBJECTIVE: The effects of rheumatoid arthritis (RA) and spondyloarthritis (SpA) on maternal and neonatal outcomes at a population level have not previously been well compared. METHODS: A contemporary pregnancy cohort of 312,081 women and corresponding birth events was assembled for the province of Alberta from the random selection of 1 live birth event per woman. We identified 3 groups: (1) no inflammatory arthritis (no IA, n = 308,989), (2) RA (n = 631), and (3) SpA (n = 2461). We compared maternal and neonatal outcomes, comorbid conditions, and medication use among the 3 groups. Multivariable logistic regression models evaluated the independent association between RA and SpA, relative to no IA, and the outcomes of small for gestation age (SGA) and hypertensive disorders during pregnancy. RESULTS: Pregnant women with RA were significantly more likely to have preterm delivery (13.5%), cesarean delivery (33.9%), hypertensive disorders in pregnancy (10.5%), and SGA babies (15.6%), compared to pregnant women with either SpA or no IA. Nonsteroidal antiinflammatory drugs and corticosteroid use were significantly higher in pregnant women with RA compared to the other groups. Women with RA were significantly more likely to have an SGA baby (OR 1.51, 95% CI 1.21-1.88; p < 0.01), and hypertensive disorder in pregnancy (OR 1.51, 95% CI 1.16-1.97; p < 0.01), compared to women with no IA, while no difference was found between women with SpA and those with no IA. CONCLUSION: Women with RA have a higher risk of worse maternal and neonatal outcomes, whereas the risk of these events is similar between women with and without SpA.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".