Postpartum complications in new mothers with juvenile idiopathic arthritis: a population-based cohort study
Bibliographic record
Abstract
Objective: The aim was to evaluate the prevalence of postpartum complications, including depression, in new mothers who had juvenile idiopathic arthritis (JIA) and to assess whether these differ from mothers who never had JIA. Methods: Our cohort study used data from physician billing and hospitalizations covering Quebec, Canada. We identified females with JIA with a first-time birth between 1 January 1983 and 31 December 2010 and assembled a control cohort of first-time mothers without JIA from the same administrative data, matching 4:1 for date of first birth, maternal age and area of residence. We compared the following postpartum complications: major puerperal infection, anaesthetic complications, postpartum haemorrhage, thromboembolism, obstetrical trauma, complications of obstetrical surgical wounds and maternal depression in the first year after delivery, in the JIA vs non-JIA groups, using bivariate analysis and multiple logistic regression. Results: The mean age at delivery was 24.7 years in the JIA group (n = 1681) and 25.0 years for the non-JIA group (n = 6724). Mothers with JIA were more likely to experience complications attributable to anaesthetic [adjusted risk ratio (aRR) 2.17, 95% CI; 1.05, 4.48], postpartum haemorrhage (aRR = 2.75, 95% CI: 2.42, 3.11) and thromboembolism (aRR = 5.27, 95% CI: 1.83, 15.17) but were at lower risk for obstetrical trauma (aRR = 0.78, 95% CI: 0.64, 0.95) or newly to develop depression in the first year postpartum (aRR = 0.52, 95% CI: 0.40, 0.68). Conclusion: Mothers with JIA appear to be at higher risk for complications attributable to anaesthesia, postpartum haemorrhage and thromboembolism. Prevention strategies for postpartum haemorrhage and thromboembolism may be especially important in this population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".