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 Background Resting heart rate (HR) is a strong established marker of risk in patients with heart failure (HF), but the clinical implications of changes in HR over time are less well established. We aimed to explore the association between visit-to-visit changes in HR and cardiovascular (CV) outcomes in a pooled participant-level dataset of 2 large cohorts of patients with HF across the full range of left ventricular ejection fraction (LVEF). Methods PARADIGM-HF and PARAGON-HF were global, multicenter, randomized clinical trials testing sacubitril/valsartan against an active control (enalapril or valsartan, respectively) in patients with HF and LVEF ≤40% (in PARADIGM-HF) or LVEF ≥45% (in PARAGON-HF). Change in HR was defined as the difference in HR between a visit at any time and the preceding visit. The association between the change in HR and subsequent risk of first HF hospitalization (HFH) or CV death was assessed using Cox proportional hazards models, after adjusting for HR at the preceding visit and potential confounders. HR at any time was also assessed using repeated measures regression models with restricted cubic splines, and was plotted relative to time defined as the number of months prior to or immediately following a HFH event or end of follow-up. Patients who experienced HFH during the study period were compared to a control population who remained free of all-cause hospitalization and all-cause death during the follow-up period. Results A total of 13,194 patients (mean age 67±11 years, 67% men, mean LVEF 40±15%) were included. Heart rates were available in 16 visits in both PARADIGM-HF and PARAGON-HF. Over a median follow-up of 2.4 years, 3,114 patients underwent a first HFH or CV death (10.4 events per 100 patient-years). Any increase in HR from the preceding visit, compared with no change, was associated with a significantly higher risk of first HFH or CV death (Figure 1, adjusted hazard ratio 1.10, 95% confidence interval, CI: 1.08–1.13, P<0.001, per 5 bpm increase in HR). Conversely, a drop in HR was associated with significantly lower risk. This prognostic association between temporal changes of HR and risk of first HFH or CV death was consistent across the range of LVEF (Pinteraction=0.34) and seen irrespective of background use of β-blockers (Pinteraction=0.91). Relative increases in HR were especially prognostic in patients without a history of atrial fibrillation/flutter (Pinteraction=0.01). HR at any time appeared to increase during the 8 months prior to a HFH event, and remained elevated after hospitalization, in comparison to a relatively stable HR observed in the control group (Figure 2). Conclusions Across a broad spectrum of patients with chronic HF, relative increases in HR from a preceding visit strongly and independently predicted both CV and non-CV outcomes. Our findings suggest that detection of notable increases in HR between outpatient visits may help identify patients at heightened risk of adverse events.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.015 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".