Sleeping on Mt Kilimanjaro—The Influence of Hypobaric Hypoxia on Brain Perfusion and Cerebral Tissue Oxygenation
Bibliographic record
Abstract
The hypobaric hypoxia encountered at high altitudes poses great challenges to the human body when adapting to these environmental conditions. Prior to full acclimatisation, a Cheyne–Stokes-like breathing pattern is commonly observed during sleep in altitude above 2500 m. We investigated the consequences of this hyperventilation and hypoventilation or apnoea on cerebral blood perfusion and tissue oxygenation during states of reduced consciousness. Perfusion and oxygen saturation of the cerebral tissue of healthy climbers were monitored with near infrared spectroscopy at night-time over the course of a six-day ascent to the summit of Mt Kilimanjaro in Tanzania. All climbers ( n = 6) experienced cyclic changes in oxygenated haemoglobin and total haemoglobin with no significant alteration of the deoxygenated haemoglobin. This is the typical pattern for periodic hypocapnic arteriolar vasoconstriction with following hypoxic vasodilation in response to blood gas changes found in Cheyne–Stokes breathing. The percentage of periodic vasoactivity increased at higher altitudes and decreased on subsequent nights at the same altitude, suggesting initial maladaptation. Conversely, cycle length decreased at greater heights and increased on subsequent nights at the same level of altitude. Periodic breathing during sleep at high altitude results in periodic changes in brain perfusion without any significant drop in tissue oxygenation. Furthermore, the results of the present investigation indicate a vasomotoric component in the pathogenesis of altitude induced headache.
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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".