Effect of air and heliox as carrier gas on CO2 transport in a model of high-frequency oscillation comparing two oscillators
Bibliographic record
Abstract
OBJECTIVE: To study the effect of carrier gas on CO(2) transport during high-frequency oscillatory ventilation in a closed model. DESIGN: In vitro model study. SETTING: Respiratory research laboratory affiliated with a tertiary center for pediatric critical care. SUBJECT: In vitro, closed-lung model consisting of a glass tube (9.8 x 1000 mm) covered at each end with balloons. INTERVENTION: Air or heliox (80:20) at constant pressure was oscillated inside the model, comparing the Sensormedics 3100A and Hummingbird BMO-20N oscillators at equal amplitude. MEASUREMENTS AND MAIN RESULTS: Tracer gas (CO(2)) was injected at one end of the model, and CO(2) concentration was measured at the opposite end. Speed of CO(2) transport was expressed as the time for the CO(2) concentration to reach 63% of the final concentration (the time constant). In room air, using the Hummingbird oscillator and increasing frequency stepwise from 5 to 20 Hz, the time constant decreased from 2813 to 457 secs (p =.05). Using the Sensormedics oscillator in room air at increasing frequency from 5 to 15 Hz, the time constant decreased from 1584 to 551 secs (p =.05). In heliox, using the Hummingbird oscillator, the speed of CO(2) transport increased by 85% (p =.029) at 5 Hz and by 28% (p =.05) at 15 Hz. With the Sensormedics oscillator using heliox, the speed of CO(2) transport increased by 16% at 5 Hz (p =.009) and 52% at 15 Hz (p =.008). Proportionally, the increase in CO(2) transport with heliox was greater at 5 Hz for the Hummingbird oscillator and at 15 Hz for the Sensormedics oscillator. CONCLUSIONS: In a closed model, we showed that during high-frequency oscillatory ventilation in room air, CO(2) transport increases with increasing frequency for both ventilators. Using heliox as carrier gas significantly augmented CO(2) transport, but the increase is frequency and device dependent. The effect of heliox on oscillator performance and the clinical applicability of our findings require further study.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".