Pregnancy Complications and Risk of Autoimmune Disease in Women: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Autoimmune diseases disproportionately impact women, and pregnancy-related events could play an underlying role. We summarized literature on the association between pregnancy complications and future risk of autoimmune disease. Materials and Methods: We systematically searched Medline, EMBASE, CINAHL Plus, and Web of Science from database inception to January 2024 for observational studies that reported on history of pregnancy complications (exposure), risk of newly diagnosed autoimmune disease (outcome), and included a comparison group of unaffected women. Two reviewers independently assessed study eligibility, extracted data, and rated risk of bias. We estimated pooled risk ratios (RRs) or odds ratios (ORs) and 95% confidence intervals (CIs) for pregnancy complications with ≥3 identified studies using DerSimonian and Laird random effects models and otherwise summarized findings following synthesis without meta-analysis (SWiM). Results: We screened 7,763 citations and included 25 studies (12 cohort, 13 case–control). Most studies were from Denmark ( n = 10) or the United Kingdom ( n = 5), with sample sizes ranging from 138 to >1.5 million women (median = 1,304 women). Risk of bias was moderate, serious, and critical in 10, 13, and 2 studies, respectively, with quality adversely impacted by potential unmeasured confounding. Meta-analyses indicated an elevated risk of autoimmune disease following preeclampsia (adjusted RR: 1.61, 95% CI: 0.98–2.65, I 2 = 90.0%) and small fetal/infant size (adjusted OR: 2.02, 95% CI: 1.16–3.52, I 2 = 28.4%), and possibly spontaneous pregnancy loss (adjusted RR: 1.58, 95% CI: 0.66–3.79, I 2 = 99.4%) and stillbirth (adjusted RR: 2.18, 95% CI: 0.65–7.34, I 2 = 99.2%), although estimates were often imprecise. SWiM findings generally supported a positive association between pregnancy complications and autoimmune disease; there were insufficient studies for gestational diabetes, placental disorders, and preterm birth. Conclusions: History of certain pregnancy complications may be a novel risk factor for autoimmune disease in women. Additional high-quality research with geographically diverse data sources would be valuable.
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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 | 0.015 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.038 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".