166 Impact of sex on the incidence of atrial fibrillation in the community: a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction Atrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with significant morbidity and mortality. By 2060, it is estimated that 18 million adults over 55 years will have AF in Europe, and significant healthcare costs are projected to accompany this substantial increase in prevalence. Sex plays a major role in its pathogenesis, but conflicting results have been reported on whether the risk of new-onset AF differs between men and women. This systematic review and meta-analysis of epidemiological studies aims to compare the incidence of new-onset AF between men and women in the community setting. Methods We searched PubMed Medline and Ovid Embase for longitudinal studies from their inception. We selected studies if they presented sex-specific incidence estimates of new-onset AF for participants without a prior history of AF recruited from the general population. We assessed the risk of bias from methodological quality using the Newcastle Ottawa Scale (NOS). We pooled data using a random-effects model with inverse-variance weighting approach, and carried out subgroup analyses to explore heterogeneity based on age and the sampling population. Risk ratio (RR) and 95% confidence interval (CI) were generated to compare the incidence of new-onset AF between men and women. Results A total of 54 prospective cohort studies met the inclusion criteria and were systematically reviewed. Of these, 45 with data on a total of 10,530,623 participants (40% women) were included in the meta-analysis. Pooled analysis demonstrated that men had a statistically significant higher risk of developing new-onset AF than women (RR 1.53; 95% CI 1.42–1.64; p < 0.00001) and this result remained robust on sensitivity analysis. The sampling population subgroup analysis suggests that the risk in men could be even higher based on studies that were part of health screening programmes (RR 2.88; 95% CI 2.16–3.83; p < 0.00001). However, the age subgroup analysis suggests that no statistically significant difference exists between the sexes beyond 50 years (RR 1.19; 95% CI 0.96–1.46; p = 0.11). Conclusion This systematic review unequivocally demonstrates that men have a higher risk of new-onset AF than women in the general population. Future research could address the usefulness of screening programmes and provide more empirical evidence for older patients. Conflict of Interest None
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.035 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".