Influence of Cheyne-Stokes respiration on ventricular response to atrial fibrillation in heart failure
Bibliographic record
Abstract
In subjects with sinus rhythm, respiration has a profound effect on heart rate variability (HRV) at high frequencies (HF). Because this HF respiratory arrhythmia is lost in atrial fibrillation (AF), it has been assumed that respiration does not influence the ventricular response. However, previous investigations have not considered the possibility that respiration might influence HRV at lower frequencies. We hypothesized that Cheyne-Stokes respiration with central sleep apnea (CSR-CSA) would entrain HRV at very low frequency (VLF) in AF by modulating atrioventricular (AV) nodal refractory period and concealed conduction. Power spectral analysis of R-wave-to-R-wave (R-R) intervals and respiration during sleep were performed in 13 subjects with AF and CSR-CSA. As anticipated, no modulation of HRV was detected at HF during regular breathing. In contrast, VLF HRV was entrained by CSR-CSA [coherence between respiration and HRV of 0.69 (SD 0.22) at VLF during CSR-CSA vs. 0.20 (SD 0.19) at HF during regular breathing, P < 0.001]. Comparison of R-R intervals during CSR-CSA demonstrated a shorter AV node refractory period during hyperpnea than apnea [minimum R-R of 684 (SD 126) vs. 735 ms (SD 147), P < 0.001] and a lesser degree of concealed conduction [scatter of 178 (SD 56) vs. 246 ms (SD 72), P = 0.001]. We conclude that CSR-CSA entrains the ventricular response to AF, even in the absence of HF respiratory arrhythmia, by inducing rhythmic oscillations in AV node refractoriness and the degree of concealed conduction that may be a function of autonomic modulation of the AV node.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".