Effect of continuous positive airway pressure on ventricular ectopy in heart failure patients with obstructive sleep apnoea
Bibliographic record
Abstract
BACKGROUND: Obstructive sleep apnoea (OSA) elicits a number of cardiovascular perturbations that could lead acutely or chronically to increased ventricular ectopy in patients with heart failure (HF). We tested the hypothesis that treatment of OSA with continuous positive airway pressure (CPAP) in patients with HF would reduce the frequency of ventricular premature beats (VPBs) during sleep in association with reduced sympathetic nervous system activity. METHODS: Following optimisation of medical treatment, 18 HF patients with OSA and >10 VPBs per hour of sleep were randomised to a control group (n = 8) or a treatment group who received CPAP (n = 10). The frequency of VPBs and urinary norepinephrine (noradrenaline) concentrations during total sleep time were determined at baseline and after 1 month. RESULTS: Control patients did not experience any significant changes in apnoea-hypopnoea index (AHI), mean nocturnal O(2) saturation, or the frequency of VPBs. In contrast, there was a significant reduction in AHI (p<0.001), an increase in minimum O(2) saturation (p = 0.05), a reduction in urinary norepinephrine concentrations (p = 0.009), and a 58% reduction in the frequency of VPBs during total sleep (from mean (SE) 170 (65) to 70 (28) per hour, p = 0.011) after 1 month of CPAP treatment. CONCLUSIONS: In patients with HF, treatment of co-existing OSA by CPAP reduces the frequency of VPBs during sleep. These data suggest that reductions in VPBs and other ventricular arrhythmias through treatment of OSA might improve the prognosis in patients with 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".