Comparison of the Ecological Footprints of administering Salbutamol by Metered-Dose Inhaler and by Nebulization in Emergency Treatment of Acute Asthma
Bibliographic record
Abstract
ABSTRACT Background The scientific evidence indicates little or no difference in the effectiveness or cost of using of metered-dose inhalers (MDIs) versus nebulization to treat acute asthma in the emergency department (ED). However, the use of MDIs raises questions of environmental impact. The objective of this study was to compare the carbon footprint of salbutamol administered by MDI versus nebulization. Methods Applying a life cycle assessment methodology, we quantified the resources extracted and pollutants emitted by each therapeutic option, from the factory production of medication and equipment to disposal by incineration. Each piece of inventory data was then translated into CO 2 -equivalent emissions (CO 2 eq) using the IPCC2021/GWP100 method. Results were estimated for the administration of 1 and 3 treatments of 800 µg of salbutamol by MDI and 5 mg by nebulization (standard doses for adults and children ≥ 24 kg) and compared to the use of a subcompact car. Results One and three ED-administered treatments with salbutamol emit respectively 1.9 and 4.0 kg of CO 2 eq via MDI versus 0.9 and 1.0 kg via nebulization, which corresponds to 5.5 km and 11.6 km and to 2.7 km and 2.8 km traveled in a subcompact car. Each series of 8 inhalations from an MDI releases 1.1 kg of CO 2 eq due to emission of the hydrofluoroalkane propellent. Interpretation Considering the absence or minimal difference in clinical effectiveness, this study suggests that nebulization may be a more eco-efficient administration route than MDIs in the emergency treatment of asthma. Trail registration N/A TAKE-HOME POINTS Study question What is the ecological footprint of metered-dose inhalers compared to nebulization for administering salbutamol when treating a patient with acute asthma in the emergency department? Results Nebulization was found to have half the carbon footprint of 1 MDI administration and one quarter of 3 MDI administrations. Interpretation Implementing low-emission treatment protocols for acute asthma should be one of many avenues to explore to achieve net-zero greenhouse gas emissions in healthcare services.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".