Is Heart Rate a Risk Marker in Patients with Chronic Heart Failure and Concomitant Atrial Fibrillation? Results from the MAGGIC Meta-Analysis
Bibliographic record
Abstract
AIM: To investigate the relationship between heart rate and survival in patients with heart failure (HF) and coexisting atrial fibrillation (AF). METHODS AND RESULTS: Patients with AF included in the Meta-analysis Global Group in Chronic Heart Failure (MAGGIC) meta-analysis were the main focus of this analysis (3259 patients from 17 studies). The outcome was all-cause mortality at 3 years. Heart rate was analysed as a categorical (tertiles; T1 ≤77 b.p.m., T2 78-98 b.p.m., T3 ≥98 b.p.m.) and continuous variable. Cox proportional hazard models were used to compare the risk of all-cause death between tertiles of baseline heart rate. Patients in the highest tertile were more often female, less likely to have an ischaemic aetiology or diabetes, had a lower ejection fraction but higher blood pressure and New York Heart Association (NYHA) class. Higher heart rate was associated with higher mortality in patients with sinus rhythm (SR) but not in those in AF. In patients with heart failure and reduced ejection fraction (HF-REF) and AF, death rates per 100 patient years were lowest in the highest heart rate tertile (T1 18.9 vs. T3 15.9) but this difference was not statistically significant (P = 0.10). In patients with heart failure and preserved ejection fraction (HF-PEF), death rates per 100 patient years were highest in the highest heart rate tertile (T1 14.6 vs. T3 16.0, P = 0.014). However, after adjustment for other important prognostic variables, higher heart rate was no longer associated with higher mortality in HF-PEF (or HF-REF). CONCLUSIONS: In this meta-analysis of patients with HF, heart rate does not have the same prognostic significance in patients in AF as it does in those in SR, irrespective of ejection fraction or treatment with beta-blocker.
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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 | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| 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 | 0.002 |
| 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".