Abstract 16466: Total Number of Pregnancies and Atrial Fibrillation Risk: The Women’s Health Study
Bibliographic record
Abstract
Introduction: Parity has been associated with an increased risk of cardiovascular disease (CVD), which is thought to be mediated by obesity and insulin resistance. However, the relationship between parity and atrial fibrillation (AF) remains unclear. Methods: We examined 34,636 female health professionals aged ≥45 years and free of AF or CVD at baseline within the Women’s Health Study. Women were prospectively followed for development of new-onset AF, which was confirmed by medical record review. Cox proportional hazards models were used to evaluate the relationship between total number of pregnancies ≥6 months in duration (0-1 [referent], 2-3, 4-5, 6) and incident AF risk. Results: During a median follow-up of 19.2 years, 1467 women developed incident AF. Median baseline age was 52.9 [IQR 48.9, 58.8] years. In multivariable analyses (Table), after adjustment for multiple confounders, including measures of socioeconomic status, hazard ratios (HR) and 95% confidence intervals (95%CI) for incident AF across categories of increasing total number of pregnancies were 1.0, 1.12 (0.94 - 1.33), 1.26 (1.04 - 1.53), and 1.37 (1.06 - 1.76). Further adjustment for time-updated changes in body mass index (BMI), hypertension, diabetes, hypercholesterolemia and other variables did not have a significant impact on these associations. Adjustment for CVD events occurring during follow-up did not significantly alter these results (fully adjusted HRs and 95%CIs across pregnancy categories: 1.0, 1.11 (0.93 - 1.32), 1.25 (1.03 - 1.52), 1.35 (1.05- 1.74); p for linear trend=0.005). Conclusions: In this large prospective cohort, number of prior pregnancies was directly associated with subsequent AF risk among women over age 45. This risk was not mediated by non-fatal CVD events, obesity, and/or diabetes. Repeated exposure to metabolic, physiological and/or hormonal changes during pregnancy may predispose to AF in later life and requires further investigation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".