Effect of increasing cerebral blood flow on sleep architecture at high altitude
Bibliographic record
Abstract
Background: Sleep at high altitude is dominated by lighter sleep stages, consistent with the fragmented sleep pattern caused by the many arousals from sleep associated with an almost universal occurrence of central sleep apnoea (CSA). Previous work has shown that pharmacologically increasing cerebral blood flow (CBF) reduces CSA severity; however, whether this alters sleep architecture is unknown. The aim of this study was to examine whether increases in CBF at high altitude affected sleep architecture and improved sleep quality. Methods: At 5050m, 11 subjects underwent full polysomnography monitored sleep following either iv acetazolamide (Az) (10mg/kg) combined with dobutamine (Dob) (2-5ug/kg/min) or placebo injections / i.v (order randomized). Duplex ultrasound of volumetric blood flow in the internal carotid and vertebral arteries was used to estimate global CBF prior to sleep. Results: CBF increased by 37±15% following Az/dob compared to placebo (P<0.001). CSA index fell from 136±47 to 49±37 events/h of sleep (P<0.001). The percentage of time spent in light sleep was less with Az/dob compared to placebo (Non-REM stage 1: 11±6% vs. 19±10; p=0.03) and there was a trend for more non-REM stage 3 sleep (21±12% vs. 13±11; p=0.06). The percentage of non-REM stage 2 was similar between conditions (62±12% vs. 58±12%, Az/dob and placebo, respectively; p=0.23), as was REM sleep (6±6% vs. 10±8%; p=0.27). All non-REM sleep stages saw a reduction in CSA events (p<0.05), whereas events during REM sleep were similar between conditions (p=0.60). Conclusion: Increasing CBF reduced the severity of CSA at high altitude, resulting in less fragmented sleep and consequently less time spent in light sleep.
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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 | 0.000 |
| 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".