Nationwide Study of Sex Differences in Incident Heart Failure in Newly Diagnosed Nonvalvular Atrial Fibrillation
Bibliographic record
Abstract
Background Heart failure (HF) is a leading complication of nonvalvular atrial fibrillation (NVAF), and the presence of both conditions worsens prognosis. Sex-specific associations between NVAF and outcomes focus on stroke; less is known about HF. We evaluated sex differences in incident HF in NVAF. Methods We identified adults age ≥ 65 years hospitalized for incident NVAF without prior HF from April 2010 to March 2018 in Canada. The primary outcome was incident HF hospitalization, with a secondary composite outcome of incident HF hospitalization or all-cause mortality at 1 year. Cox proportional hazard regression models were constructed for the association between sex and outcomes, adjusting for age, comorbidities, socioeconomic status, cardioversion, and medications. Results Of 68,909 NVAF patients, 53.8% were women. Women had a higher rate of the primary outcome (30.0% vs 25.6%, P < 0.001) and the composite outcome (39.5% vs 36.6%, P < 0.001) than men. In multivariable analysis without adjusting for medications, there was an 8% increase risk of HF (95% confidence interval [CI] 1.05-1.11, P < 0.001) for women, which was attenuated when accounting for medication (hazard ratio [HR] 1.01, 95% CI 0.98-1.04). After full adjustment, women age ≥ 75 years were at higher risk of the primary outcome (HR 1.10, 95% CI 1.06-1.13, P < 0.001) and the composite outcome (HR 1.04, 95% CI 1.01-1.07, P < 0.001), compared with men, whereas there was a significantly lower risk for those age 65-75 years. Conclusions In this nationwide study of incident NVAF without HF, women age ≥ 75 years were more likely to develop HF or die than men. Strategies to prevent HF in older women with NVAF are needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".