Low resting heart rates are associated with new‐onset atrial fibrillation in patients with vascular disease: results of the <scp>ONTARGET</scp>/<scp>TRANSCEND</scp> studies
Bibliographic record
Abstract
BACKGROUND: Elevated systolic blood pressure (SBP) and high resting heart rate (HR) are associated with cardiovascular end-points. Although the association between atrial fibrillation (AF) and SBP is well established, the relation between AF and HR remains unclear. METHODS: In patients from the ONTARGET and TRANSCEND studies with high cardiovascular disease risk (n = 27 064), new-onset AF was evaluated in relation to mean SBP, visit-to-visit variation in SBP (SBP-CV; i.e. SD/mean × 100%), mean HR and visit-to-visit variation in HR (HR-CV). RESULTS: Low mean HR (P < 0.0001) and high SBP (P = 0.0021) were associated with incident AF. High SBP-CV (P = 0.031) and HR-CV (P < 0.0001) were also associated with incident AF. After adjustment for confounders, SBP and SBP-CV were no longer significantly associated with AF. The detrimental effect of low HR was particularly evident in subjects who were not receiving treatment with beta-blockers (P = 0.014 for interaction between beta-blocker use and mean HR). In addition to low HR, high HR-CV and high SBP had additive effects on incident AF. CONCLUSIONS: Low mean HR (<60 beats min(-1) ) is independently associated with incident AF, and low HR-CV and high SBP further increase the incidence of new-onset AF in patients at high risk of cardiovascular disease.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".