Testing of Nebulizers for Delivering Magnesium Sulfate to Pediatric Asthma Patients in the Emergency Department
Bibliographic record
Abstract
BACKGROUND: As the use of intravenous magnesium sulfate (MgSO(4)) for the treatment of refractory asthma is becoming more common, the incidence of MgSO(4)-related systemic hypotension is also rising. One option is to deliver MgSO(4) via aerosol, but compared to most inhaled medications, which are active in the microgram dose range, the MgSO(4) dose requirement is in the milligram range. This, along with inefficient aerosol delivery systems, may be the reason that some studies have found lack of efficacy with aerosol MgSO(4). In preparation for a multicenter study of inhaled MgSO(4) in asthmatic children 2-17 years old, we conducted an in vitro study to choose the best MgSO(4) nebulizer system that would be effective over the entire age range. METHODS: We tested the Pari LC Star jet nebulizer, Omron MicroAir vibrating-mesh nebulizer, and the Aeroneb Go vibrating-mesh nebulizer with the Idehaler valve-less holding chamber. Aerosol delivery was via face mask. RESULTS: The Pari LC Star had an appropriate particle size distribution but a very slow aerosol output rate. The Omron MicroAir had an even slower output rate and a larger particle size distribution, which would be inappropriate for smaller children. In vitro lung deposition with the Aeroneb Go with Idehaler was 16.0 ± 0.4 mg/min in older children and approximately a fifth of that in toddlers. CONCLUSIONS: The Aeroneb Go with Idehaler was chosen for the multicenter clinical 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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".