Patient‐reported outcomes and subsequent management in atrial fibrillation clinical practice: Results from the Utah mEVAL AF program
Bibliographic record
Abstract
BACKGROUND: Atrial fibrillation (AF) significantly reduces health-related quality of life (HRQoL), previously measured in clinical trials using patient-reported outcomes (PROs). We examined AF PROs in clinical practice and their association with subsequent clinical management. METHODS: The Utah My Evaluation (mEVAL) program collects the Toronto AF Symptom Severity Scale (AFSS) in AF outpatients at the University of Utah. Baseline factors associated with worse AF symptom score (range 0-35, higher is worse) were identified in univariate and multivariable analyses. Secondary outcomes included AF burden and AF healthcare utilization. We also compared subsequent clinical management at 6 months between patients with better versus worse AF HRQoL. RESULTS: Overall, 1338 patients completed the AFSS symptom score, which varied by sex (mean 7.26 for males vs. 10.27 for females; p < .001), age (<65, 9.73; 65-74, 7.66; ≥75, 7.58; p < .001), heart failure (9.39 with HF vs. 7.67 without; p < .001), and prior ablation (7.28 with prior ablation vs. 8.84; p < .001). In multivariable analysis, younger age (mean difference 2.92 for <65 vs. ≥75; p < .001), female sex (mean difference 2.57; p < .001), pulmonary disease (mean difference 1.88; p < .001), and depression (mean difference 2.46; p < .001) were associated with higher scores. At 6-months, worse baseline symptom score was associated with the use of rhythm control (37.1% vs. 24.5%; p < .001). Similar cofactors and results were associated with increased AF burden and health care utilization scores. CONCLUSIONS: AF PROs in clinical practice identify highly-symptomatic patients, corroborating findings in more controlled, clinical trials. Increased AFSS score correlates with more aggressive clinical management, supporting the utility of disease-specific PROs guiding clinical practice.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".