Identification and Validation of Nebulized Aerosol Devices for Sputum Induction
Bibliographic record
Abstract
BACKGROUND: Induced sputum cell counts are a noninvasive and reliable method for evaluating the presence, type and degree of airway inflammation in patients with asthma. Currently, standard nebulizer devices used for sputum induction in multiple patients are labelled as single-patient devices by the manufacturer, which conflicts with infection prevention and control requirements. As such, these devices cannot feasibly be used in a clinical sputum induction program. Therefore, there is a need to identify alternative nebulizer devices that are either disposable or labelled for multipatient use. OBJECTIVE: To apply validated rigorous, scientific testing methods to identify and validate commercially available nebulizer devices appropriate for use in a clinical sputum induction program. METHODS: Measurement of nebulized aerosol output and size for the selected nebulizer designs followed robust International Organization for Standardization methods. Sputum induction using two of these nebulizers was successfully performed on 10 healthy adult subjects. The cytotechnologist performing sputum cell counts was blinded to the type of nebulizer used. RESULTS: The studied nebulizers had variable aerosol outputs. The AeroNeb Solo (Aerogen, Ireland), Omron NE-U17 (Omron, Japan) and EASYneb II (Flaem Nuova, Italy) systems were found to have similar measurements of aerosol size. There was no significant difference in induced sputum cell results between the AeroNeb Solo and EASYneb II devices. DISCUSSION: There is a need for rigorous, scientific evaluation of nebulizer devices for clinical applications, including sputum induction, for measurement of cell counts. CONCLUSION: The present study was the most comprehensive analysis of different nebulizer devices for sputum induction to measure cell counts, and provides a framework for appropriate evaluation of nebulizer devices for induced sputum testing.
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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 | 0.001 | 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) | 0.000 | 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".