Visit-to-Visit Changes in Heart Rate in Heart Failure: A Pooled Participant-Level Analysis of the PARADIGM-HF and PARAGON-HF Trials
Bibliographic record
Abstract
Abstract Aims Resting heart rate (HR) is a strong risk marker in patients with heart failure (HF), but the clinical implications of visit-to-visit changes in HR (ΔHR) are less well established. We aimed to explore the association between ΔHR and subsequent outcomes in a pooled dataset of two well-characterized cohorts of patients with HF across the full range of left ventricular ejection fraction (LVEF). Methods and results PARADIGM-HF and PARAGON-HF were randomized trials testing sacubitril/valsartan versus enalapril or valsartan, respectively, in patients with HF and LVEF ≤40% (PARADIGM-HF) or LVEF ≥45% (PARAGON-HF). We analysed the association between ΔHR from the preceding visit with the primary endpoint of HF hospitalization (HFH) or cardiovascular death using covariate-adjusted Cox proportional hazards models. A total of 13 194 patients (mean age 67 ± 11 years, 67% men, mean LVEF 40 ± 15%) were included. Over a median follow-up of 2.5 years, 3114 patients experienced a first HFH or cardiovascular death event (10.4 events per 100 patient-years). An increase in HR from the preceding visit, compared with no change, was associated with a higher risk (hazard ratio 1.12; 95% confidence interval [CI] 1.10–1.15; p < 0.001 per 5 bpm increase). Conversely, a drop in HR was associated with a lower risk (hazard ratio 0.97; 95% CI 0.94–1.00; p = 0.044 per 5 bpm drop). The prognostic implications of ΔHR were consistent across the range of LVEF and observed regardless of β-blocker use or presence of a permanent pacemaker. Visit-to-visit increases in HR were especially prognostic in patients without atrial fibrillation (pinteraction = 0.006). Conclusion Across a broad spectrum of patients with chronic HF, increases in HR from a preceding visit independently predicted clinical outcomes. The detection of notable increases in HR between outpatient visits may help identify patients at heightened risk of adverse events. Clinical Trial Registration: ClinicalTrials.gov NCT01035255 (PARADIGM-HF), NCT01920711 (PARAGON-HF).
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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 | 0.018 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.018 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".