Electroencephalographic (EEG) changes accompanying normal breathing of concentrated oxygen (hyperoxic ventilation) by healthy adults: a systematic review
Bibliographic record
Abstract
Introduction: Divers often increase their fraction of inspired oxygen (FIO₂) to decrease their risk of decompression sickness. However, breathing elevated pressures of oxygen can cause central nervous system oxygen toxicity (CNS-OT). This study aimed to review the literature describing the effect of hyperoxia on the electroencephalogram (EEG), thus exploring the potential for real-time detection of an impending CNS-OT seizure. Methods: We searched Medline, Embase, Scopus, and Web of Science for articles that reported EEG measures accompanying hyperoxic ventilation (FIO₂ = 1.0 ± hyperbaric pressure) in healthy participants. We included peer-reviewed journal articles, books, and government reports with no language or date restrictions. Randomised controlled trials and cross-over studies were included; case reports were excluded. We used the Newcastle-Ottawa scale to evaluate evidence quality. Results: Our search strategy returned 1,025 unique abstracts; we analysed the full text of 46 articles; 22 articles (16 studies) were included for review. Study cohorts were typically small and comprised of male non-divers. We discovered a variety of EEG analysis methods: studies performed spectral analysis (n = 12), the analysis of sensory-evoked potentials (n = 4), connectivity/complexity analysis (n = 3), source localisation (n = 1), and expert qualitative analyses (n = 4). Studies of severe exposures (long duration at hyperbaric pressure) typically reported qualitative measures, and studies of mild exposures typically reported quantitative measures. Conclusions: There is a need for a large randomised controlled trial reporting quantitative measures to better understand the effect of hyperoxia on the EEG, thus enabling the development of real-time monitoring of CNS-OT risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".