Health-Related Quality of Life in Patients With Atrial Fibrillation Treated With Rhythm Control Versus Rate Control
Bibliographic record
Abstract
BACKGROUND: Improving health-related quality of life (HRQoL) is an important treatment goal in the management of patients with atrial fibrillation (AF). Uncertainty exists as to whether patients' HRQoL differ when treated with medical rhythm control or rate control. We compared HRQoL between patients treated with rhythm control or rate control in a large observational registry of patients with recent-onset AF. METHODS AND RESULTS: In the Registry on Cardiac Rhythm Disorders Assessing the Control of Atrial Fibrillation (RECORD-AF), 2439 patients with recent onset (<1 year) AF completed an AF-specific HRQoL questionnaire, the University of Toronto Atrial Fibrillation Severity Scale. HRQoL was assessed by the AF symptom severity score (0-35, with higher scores reflecting more severe AF-related symptoms) at baseline and 1 year. The minimal clinically important difference was defined as a change of ≥3 points. The primary analysis was based on a propensity score-adjusted longitudinal regression analysis which compared the change in AF symptom severity scores between the 2 groups. Over an average follow-up of 1 year, the AF symptom severity scores improved in both groups (rhythm control: -2.82 point [95% confidence interval, -3.22 to -2.41]; rate control: -2.11 point [95% confidence interval, -2.54 to -1.67]; P<0.01 for both groups). The magnitude of improvement was higher in the rhythm control group than the rate control group (unadjusted difference: -0.75 point; 95% confidence interval, -1.31 to -0.19; P=0.01; propensity score-adjusted difference: -0.71 point; 95% confidence interval, -1.31 to -0.11; P=0.02). CONCLUSIONS: In this observational cohort of recent-onset AF patients, treatment with medical rhythm- or rate control over 1 year was associated with an improvement in HRQoL. The magnitude of HRQoL improvement was minimally higher in patients treated with rhythm control than rate control. However, the overall degree of improvement was not large, and its clinical significance was uncertain.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".