A narrative review of periodic breathing during sleep at high altitude: From acclimatizing lowlanders to adapted highlanders
Bibliographic record
Abstract
Periodic breathing during sleep at high altitude is almost universal among sojourners. Here, in the context of acclimatization and adaptation, we provide a contemporary review on periodic breathing at high altitude, and explore whether this is an adaptive or maladaptive process. The mechanism(s), prevalence and role of periodic breathing in acclimatized lowlanders at high altitude are contrasted with the available data from adapted indigenous populations (e.g. Andean and Tibetan highlanders). It is concluded that (1) periodic breathing persists with acclimatization in lowlanders and the severity is proportional to sleeping altitude; (2) periodic breathing does not seem to coalesce with poor sleep quality such that, with acclimatization, there appears to be a lengthening of cycle length and minimal impact on the average sleeping oxygen saturation; and (3) high altitude adapted highlanders appear to demonstrate a blunting of periodic breathing, compared to lowlanders, comprising a feature that withstands the negative influences of chronic mountain sickness. These observations indicate that periodic breathing persists with high altitude acclimatization with no obvious negative consequences; however, periodic breathing is attenuated with high altitude adaptation and therefore potentially reflects an adaptive trait to this environment.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".