Therapeutic Considerations in Applying Rate Control Therapy for Atrial Fibrillation
Bibliographic record
Abstract
The therapeutic strategy of heart rate control for atrial fibrillation (AF) is undergoing a renaissance since several recent randomized trials demonstrated clear advantages over the rhythm control for many patients. Heart rate control for AF is hampered, however, by a dearth of information relating target heart rates to physiological measures or clinical outcomes. In this review, the rather sparse rationale behind the data elements for heart rate control - resting heart rate, activity heart rate, and regularity of the heart rate, is outlined. Beat-to-beat stroke volume is probably a key variable for calibrating heart rate targets. Presently it seems reasonable to propose targets for resting and activity heart rates but not for regularity. It also seems plausible but remains unproven that there should be a range (upper and lower) of heart rate targets rather than a simple upper limit. Nevertheless, it remains to be demonstrated through randomized clinical trials how to apply various heart rate control targets in patients with AF and whether complexity offers any advantage over simplicity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".