Impact of Resting Heart Rate at 30 Days Following Transcatheter or Surgical Aortic Valve Replacement and Cardiovascular Outcomes: Insights from The PARTNER 2 Trial
Bibliographic record
Abstract
Background Elevated resting heart rate (RHR) is associated with adverse cardiovascular outcomes in patients with untreated aortic valve stenosis (AS). However, the impact of RHR following transcatheter (TAVR) or surgical aortic valve replacement (SAVR) on cardiovascular outcomes is unknown. We therefore sought to determine the effect of RHR at 30 days after aortic valve replacement (AVR) on 2-year outcomes in patients with severe symptomatic AS. Methods The study population consists of 3170 patients from the PARTNER 2 Trial and its embedded registries who underwent TAVR or SAVR for severe AS, and had available 12-lead electrocardiograms demonstrating sinus rhythm at 30 days post-procedure. Outcomes at 2 years were analyzed according to 30-day RHR modeled as a continuous variable and in groups (RHR ≥75 bpm and RHR <75 bpm). Results By multivariable analysis, RHR ≥75 bpm at 30 days after AVR was an independent predictor of the composite endpoint of all-cause death, rehospitalization or stroke (hazard ratio [HR] 1.26, 95% confidence interval [CI], 1.05–1.52, p = 0.015) and rehospitalization (HR 1.42, 95% CI, 1.12–1.79, p = 0.004). Similarly, RHR modeled as a continuous variable (per 5 bpm) remained an independent predictor of all-cause death, rehospitalization or stroke (adjusted HR 1.07, 95% CI, 1.03–1.11, p = 0.0007), and rehospitalization (adjusted HR 1.09, 95% CI, 1.04–1.14, p = 0.0003) at 2 years. Conclusions In patients with severe AS treated with TAVR or SAVR, resting heart rate at 30 days post-procedure was an independent predictor of the composite endpoint of all-cause death, rehospitalization or any stroke, and of rehospitalization at 2 years.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".