Elevated Waste Anaesthetic Gas Concentration in the Paediatric Post-Anaesthesia Care Unit
Bibliographic record
Abstract
OBJECTIVE: Exposure to waste anaesthetic gas (WAG) is a recognised occupational hazard for health care professionals (HCP). In recovery rooms, scavenging and ventilation systems differ from those in the operating room, raising the question as to how efficient they are. This study aims to measure the levels of ambient sevoflurane over the course of consecutive workdays in the paediatric recovery room of a tertiary academic centre. METHODS: The following is a descriptive-analytic study of ambient air sevoflurane levels measured using a MIRAN® 205B Series SapphIRe portable ambient air analyser. Samples were obtained between 7:30 am and 6:30 pm for two non-consecutive weeks on consecutive weekdays in our paediatric recovery room area. RESULTS: The ambient air levels of sevoflurane exceeded the ceiling concentration of 0.5 ppm recommended by the National Institute for Occupational Safety and Health on all days of measurement. The concentration of sevoflurane in ambient air correlates directly with the number of patients present. CONCLUSION: Even in a modern recovery room constructed according to current building standard and code, ambient air levels of WAG exceed the recommendations. Future research and practice standards are needed to reduce this occupational exposure. Disregarding whether chronic exposure to WAG is harmful, we have shown that HCP working in recovery rooms are chronically exposed to concentrations which exceed recommended levels. Strategies are needed to reduce ambient levels of WAG in post-anaesthesia care units.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".