Does Use Of A Heat and Moisture Exchanger Affect pMDI Delivery to a Simulated Patient on Mechanical Ventilation
Bibliographic record
Abstract
Objective: Heat and moisture exchangers (HME) have been designed to allow aerosol delivery to mechanically ventilated patients by bypassing the HME during aerosol administration. This study evaluates the effect a bypass-type HME has on aerosol delivery in a simulated adult ventilator setting. Methods: A Fisher & Paykel RT210 adult breathing circuit was used to simulate an adult model (500mL, duty cycle = 33%, 13 bpm) generated using a Draeger Infinity C500 ventilator. A Gibeck Humid-Flo HME was placed at the entrance to an 8.0mm diameter endotracheal tube (ETT). An aerosol collection filter was located at the distal end of the ETT and coupled to a SelfTestLung, simulating the patient. 5 actuations of Ventolin pMDI were delivered through 3 different delivery devices and a built-in port adapter in the circuit, followed by 6 complete breathing cycles. Salbutamol assay was undertaken by HPLC-UV. Comparisons were made on potential dose to the lungs and were equated to a potential relative carbon footprint based upon published claims [1] for Ventolin. Results: Conclusions: This study has shown that use of a bypass-type HME can allow delivery of medication to the patient. It also demonstrates that use of AeroChamber* VENT HC spacer could potentially reduce the carbon footprint by up to 4-fold compared to the alternative options. By maximizing the amount of each puff reaching the lungs the patient is likely to get relief sooner and reduce the number of puffs needed. erj;64/suppl_68/PA2613/TB1 T1 TB1 Device Total Mass of Salbutamol /Actuation (mean ± SD) AeroChamber* VENT HC 33.1±2.7µg Spirale DDS 7.7±3.0µg Hudson RCI MDI Adaptor 20.2±3.9µg Built-in circuit pMDI port 22.9±1.2µg [1] https://greeninhaler.org
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".