Nebulization of Lidocaine with Varied Oxygen Flow Rates
Bibliographic record
Abstract
To the Editor: The delivery of lidocaine via small-volume nebulizers (SVN) can be used as topical anesthesia for use during flexible bronchoscopy in infants and children. Although the SVN is small and easy to use, the rate of nebulization at different gas flow rates is not well known. Since the total amount of nebulized lidocaine delivered to pediatric patients in relation to time and flow rates is important to prevent lidocaine toxicity (1), we recently conducted an in vitro study that evaluated the rate of nebulization of lidocaine with differential oxygen flow rates. Five SVNs (Misty-Neb Nebulizer, Allegiance, IL) were studied. Each SVN was filled with 5 mL of 4% lidocaine and connected to a pediatric facemask. The SVN was connected to the dispensing oxygen at flow rates of 2, 3, 4, 5, 6, 7, 8, and 10 L/min, respectively. The dispensing oxygen was temporarily stopped at 5-min intervals and the lidocaine was allowed to settle in the SVN to measure the residual volume. On the basis of the results of this study (Fig. 1), the amount of lidocaine nebulized at different oxygen flow rates and time periods can be estimated. This information may be used to limit the possible maximum lidocaine delivered to the patient by adjusting gas flow rates and reducing time exposure. Other brands of SVN may need separate calibration, as this study only examined one particular brand.Figure 1: Rate of nebulization of lidocaine with varied oxygen flow rates.Ban Ch. Tsui, MD, MSC, FRCP(C)) Stephan Malherbe, MB, ChB, MMed, FCA(SA)
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".