Time course of continuous positive airway pressure effects on central sleep apnoea in patients with chronic heart failure
Bibliographic record
Abstract
Continuous positive airway pressure (CPAP) causes a variable immediate reduction in the frequency of central apnoeas and hypopnoeas in patients with congestive heart failure (CHF) and central sleep apnoea (CSA), but has beneficial mid-term effects on factors known to destabilize the ventilatory control system. We, therefore, tested whether CPAP therapy leads, in addition to its short-term effects on CSA, to a significant further alleviation of CSA after 12 weeks of treatment on the same CPAP level in such patients. CPAP therapy was initiated in 10 CHF patients with CSA. During the first night on CPAP, the pressure was stepwise increased to a target pressure of 8-12 cmH(2)O or the highest level the patients tolerated (<12 cmH(2)O). Throughout the second night (baseline CPAP), the achieved CPAP of the first night was applied. After 12 weeks of CPAP treatment, we performed a follow-up polysomnography (12 weeks CPAP) on the same CPAP level (8.6 +/- 1.1 cmH(2)0). We found a significant reduction of the apnoea-hypopnoea index (AHI) between the diagnostic polysomnography and baseline CPAP night (41.8 +/- 19.2 versus 22.2 +/- 12.6 events per hour; P = 0.005). The AHI further significantly decreased between the baseline CPAP night and the 12 weeks CPAP night on the same CPAP level (22.2 +/- 12.6 versus 12.8 +/- 11.0 events per hour; P = 0.028). We conclude that, in addition to its immediate effects, CPAP therapy leads to a time-dependent alleviation of CSA in some CHF patients, indicating that in such patients neither clinical nor scientific decisions should be based on a short-term trial of CPAP.
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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 | 0.000 | 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".