End tidal-to-arterial CO<sub>2</sub>and O<sub>2</sub>gas gradients at low- and high-altitude during dynamic end-tidal forcing
Bibliographic record
Abstract
We sought to characterize and quantify the performance of a portable dynamic end-tidal forcing (DEF) system in controlling the partial pressure of arterial CO2 (Pa(CO2)) and O2 (Pa(O2)) at low (LA; 344 m) and high altitude (HA; 5,050 m) during an isooxic CO2 test and an isocapnic O2 test, which is commonly used to measure ventilatory and vascular reactivity in humans (n = 9). The isooxic CO2 tests involved step changes in the partial pressure of end-tidal CO2 (PET(CO2)) of -10, -5, 0, +5, and +10 mmHg from baseline. The isocapnic O2 test consisted of a 10-min hypoxic step (PET(O2) = 47 mmHg) from baseline at LA and a 5-min euoxic step (PET(O2) = 100 mmHg) from baseline at HA. At both altitudes, PET(O2) and PET(CO2) were controlled within narrow limits (<1 mmHg from target) during each protocol. During the isooxic CO2 test at LA, PET(CO2) consistently overestimated Pa(CO2) (P < 0.01) at both baseline (2.1 ± 0.5 mmHg) and hypercapnia (+5 mmHg: 2.1 ± 0.7 mmHg; +10 mmHg: 1.9 ± 0.5 mmHg). This P(a)-PET(CO2) gradient was approximately twofold greater at HA (P < 0.05). At baseline at both altitudes, PET(O2) overestimated Pa(O2) by a similar extent (LA: 6.9 ± 2.1 mmHg; HA: 4.5 ± 0.9 mmHg; both P < 0.001). This overestimation persisted during isocapnic hypoxia at LA (6.9 ± 0.6 mmHg) and during isocapnic euoxia at HA (3.8 ± 1.2 mmHg). Step-wise multiple regression analysis, on the basis of the collected data, revealed that it may be possible to predict an individual's arterial blood gases during DEF. Future research is needed to validate these prediction algorithms and determine the implications of end-tidal-to-arterial gradients in the assessment of ventilatory and/or vascular reactivity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".