Pregnancy and the Risk of Rheumatoid Arthritis in a Highly Predisposed North American Native Population
Bibliographic record
Abstract
OBJECTIVE: To examine reproductive history and rheumatoid arthritis (RA) risk in a highly predisposed population of North American Natives (NAN) with unique fertility characteristics. METHODS: The effect of pregnancy on the risk of RA was examined by comparing women enrolled in 2 studies: a study of RA in NAN patients and their unaffected relatives; and NAN patients with RA and unrelated healthy NAN controls enrolled in a study of autoimmunity. All participants completed questionnaires detailing their reproductive history. RESULTS: Patients with RA (n = 168) and controls (n = 400) were similar overall in age, education, shared epitope frequency, number of pregnancies, age at first pregnancy, smoking, and breastfeeding history. In multivariate analysis, for women who had ≥ 6 births the OR for developing RA was 0.43 (95% CI 0.21-0.87) compared with women who had 1-2 births (p = 0.046); for women who gave birth for the first time after age 20 the OR for developing RA was 0.33 (95% CI 0.16-0.66) compared with women whose first birth occurred at age ≤ 17 (p = 0.001). The highest risk of developing RA was in the first postpartum year (OR 3.8; 95% CI 1.45-9.93) compared with subsequent years (p = 0.004). CONCLUSION: In this unique population, greater parity significantly reduced the odds of RA; an early age at first birth increased the odds, and the postpartum period was confirmed as high risk for RA onset. The protective effect of repeated exposure to the ameliorating hormonal and immunological changes of pregnancy may counterbalance the effect of early exposure to the postpartum reversal of these changes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".