Atrial Fibrillation Begets Heart Failure and Vice Versa
Bibliographic record
Abstract
BACKGROUND: Atrial fibrillation (AF) and heart failure (HF) frequently coexist and together confer an adverse prognosis. The association of AF with HF subtypes has not been well described. We sought to examine differences in the temporal association of AF and HF with preserved versus reduced ejection fraction. METHODS AND RESULTS: We studied Framingham Heart Study participants with new-onset AF or HF between 1980 and 2012. Among 1737 individuals with new AF (mean age, 75±12 years; 48% women), more than one third (37%) had HF. Conversely, among 1166 individuals with new HF (mean age, 79±11 years; 53% women), more than half (57%) had AF. Prevalent AF was more strongly associated with incident HF with preserved ejection fraction (multivariable-adjusted hazard ratio [HR], 2.34; 95% confidence interval [CI], 1.48-3.70; no AF as referent) versus HF with reduced ejection fraction (HR, 1.32; 95% CI, 0.83-2.10), with a trend toward difference between HF subtypes (P for difference=0.06). Prevalent HF was associated with incident AF (HR, 2.18; 95% CI, 1.26-3.76; no HF as referent). The presence of both AF and HF portended greater mortality risk compared with neither condition, particularly among individuals with new HF with reduced ejection fraction and prevalent AF (HR, 2.72; 95% CI, 2.12-3.48) compared with new HF with preserved ejection fraction and prevalent AF (HR, 1.83; 95% CI, 1.41-2.37; P for difference=0.02). CONCLUSIONS: AF occurs in more than half of individuals with HF, and HF occurs in more than one third of individuals with AF. AF precedes and follows HF with both preserved and reduced ejection fraction, with some differences in temporal association and prognosis. Future studies focused on underlying mechanisms of these dual conditions are warranted.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".