Changes in heart rate variability in subjects exposed to ten days intermittent hypoxia
Bibliographic record
Abstract
Exogenous hypoxia as a training method leads to adaptations, many of which are related to a change in the activity of the autonomic nervous system. Aim: To assess the alterations in heart rate variability (HRV) in subjects, exposed to one hour of exogenous hypoxia in the course of ten consecutive days. Material and methods:Twelve healthy non-smoker males aged 29.84±7.43 (mean±SD) were subjected to one-hour hypoxic sessions over ten consecutive days (FiO 2 =12.3±1.5%) via hypoxicator (Altitude Tech, AltiPro 8850 Summit+, Canada)with simultaneous recording of electrocardiography and pulse oxymetry. HRV data was derived via specific software (Kubios HRV, Finland) by analyzing the one-hour hypoxic period. Results: Comparing the last visit to the first the subjects had lower normalized low frequency power (LF) (66.83±14.64vs 55.92±13.39; p=0.032) and higher high frequency power (HF) (34.07±14.08 vs 44.07±103.39; p=0.050) as well as lower LF/HF ratio (2.43±1.39 vs 1.52±0.96; p=0.026) and higher total power (4887.0±4324.2 vs 6875.8±4399.1; p=0.035). The subjects also had a higher standard deviation of normal-to-normal inter-beat intervals (SDNN) (65.67±32.46 vs 81.08±31.95; p=0.013), and a higher root mean square of successive difference (RMSSD) (58.08±30.87 vs 76.46±34.56; p=0.029). Conclusion:Exposure to exogenous hypoxia for one hour over ten consecutive days leads to changes in HRV – a reduction in LF and LF/HF ratio and an elevation in HF and total power as well as SDNN and RMSSD. In the course of an intermittent hypoxic protocol sympathetic tone decreases in contrast to an increase in parasympathetic tone. The overall activity of the autonomic nervous system also increases.
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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".