Heart Disease, Hypertension, Gestational Diabetes Mellitus, and Preeclampsia/Eclampsia in Mothers With Juvenile Arthritis: A Nested Case–Control Study
Bibliographic record
Abstract
OBJECTIVE: To determine whether women with a history of juvenile arthritis are at higher risk for heart disease and hypertension and for developing adverse maternal outcomes: gestational diabetes mellitus, maternal hypertension, and preeclampsia/eclampsia. METHODS: We designed a nested case-control study from a cohort of first-time mothers with prior physician billing codes suggesting juvenile arthritis, and a matched comparison group without juvenile arthritis. For the nested case-control design, we selected 3 controls for each case for the outcomes of heart disease (n = 403), prepregnancy hypertension (n = 66), gestational diabetes mellitus (n = 285), maternal hypertension (n = 561), and preeclampsia/eclampsia (n = 236). We used conditional logistic regression, adjusting for maternal age and education. RESULTS: Having juvenile arthritis was associated with heart disease (odds ratio [OR] 2.44 [95% confidence interval (95% CI) 1.15-5.15]) but not with gestational hypertension, diabetes mellitus, or preeclampsia/eclampsia. All 66 cases of prepregnancy hypertension had juvenile arthritis. Having prepregnancy hypertension was strongly associated with preeclampsia/eclampsia (OR 8.05 [95% CI 2.69-24.07]). CONCLUSION: Women with a history of juvenile arthritis had a higher risk of heart disease. This risk signals the potential importance of cardiac prevention strategies in juvenile arthritis. As this was a retrospective study, it was not possible to correct for some relevant potential confounders. Further studies should assess the impact of medications, disease severity, and other factors (e.g., obesity) on cardiac outcomes in juvenile arthritis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".