Activity‐Responsive Pacing Produces Long‐Term Heart Rate Variability
Bibliographic record
Abstract
INTRODUCTION: Long-term heart rate variability (HRV) measures, including the standard deviation of means of successive 5-minute epochs of R-R interval intervals (SDANN) and the power law slope (beta), are important prognostic measures, yet their physiologic basis is unknown. We tested the hypothesis that long-term HRV arises from physical activity in a randomized cross-over study in patients with rate-responsive pacemakers. METHODS AND RESULTS: Ten patients with complete heart block and dual-chamber pacemakers underwent 24-hour periods of ambulatory ECG in each of three pacing modes: atrially tracked, fixed-rate, and rate-responsive pacing. SDANN, ultra low frequency (ULF; frequencies <0.0033 Hz), and beta slope were calculated; and high-frequency power and root mean square of consecutive normal R-R intervals (rMSSD) were calculated as measures of short-term HRV, which have autonomic origins. Long-term HRV measures were similar with atrially tracked and rate-responsive pacing and were much greater than in fixed-rate pacing (SDANN P = 0.0001; ULF P = 0.0001; beta slope P = 0.0002). Short-term HRV measures were similarly low in fixed-rate and rate-responsive pacing (P = NS) and were significantly lower than with atrially tracked pacing (P = 0.0034). CONCLUSION: Rate-responsive pacing reproduces long-term, but not short-term, measures of HRV, suggesting that they may be markers of heart rate responses to patient activity.
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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) | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".