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Record W4416193245 · doi:10.1002/resp.70157

Climate Change and Respiratory Care With Inhalers

2025· article· en· W4416193245 on OpenAlexaboutno aff
Fanny W.S. Ko

Bibliographic record

VenueRespirology · 2025
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeGreenhouse gasExtreme weatherStormGlobal warmingMistTropical cycloneAir pollution

Abstract

fetched live from OpenAlex

The escalating impacts of climate change became starkly personal for me this year when Super Typhoon Raggasa disrupted international travel, forcing complex flight rearrangements to attend an important academic meeting. This echoed a similar experience just months earlier, when a tropical storm in my home town led to flight cancellation and stranded me in London for several days. Climate-driven extreme weather events are increasing in frequency and intensity, and climate change exacerbates respiratory diseases through multiple pathways, including altered allergen exposures, increased air pollution, and more frequent extreme weather events (https://doi.org/10.1183/20734735.0222-2022). Paradoxically, the inhalers we use to treat airway diseases contribute to the problem. Among the three main types of inhalers, metered-dose inhalers (MDIs), dry powder inhalers (DPIs) and soft mist inhalers, MDIs contain hydrofluoroalkane (HFA) propellants, are potent greenhouse gases with global warming potential thousands of times more powerful than carbon dioxide (https://www.ipcc.ch/assessment-report/ar4/). A recent study found that 1.6 billion inhalers were dispensed in the United States from 2014 to 2024, generating an estimated 24.9 million metric tons of carbon dioxide equivalent, with MDIs responsible for 98% of this climate pollution from inhalers (https://doi.org/10.1001/jama.2025.16524). The medical community has faced similar challenges before, having successfully phased out ozone-depleting chlorofluorocarbon inhalers in the previous decade (https://doi.org/10.2147/DDDT.S262141). We must again innovate toward sustainability. The US Veterans Health Administration demonstrates that a substantial environmental benefit of prioritising DPIs over traditional MDIs could reduce planet-warming gases from inhalers by more than 68% between 2008 and 2023 (https://doi.org/10.1001/jama.2025.15638). As healthcare providers, we must balance environmental concerns with optimal patient care. Not all patients can transition to low-carbon alternatives—young children, older adults, and those with severely compromised lung function may still require MDIs. DPIs require the ability to generate sufficient inspiratory flow, which can be challenging during acute exacerbations or for patients with physical limitations. Cost, availability and ability to master the technique of using inhalers are also important considerations. Shared decision-making between health professionals and patients about the choice of inhalers is thus crucial (https://doi.org/10.1016/S0140-6736(23)01358-2). Beyond device selection, we can advocate for broader systemic changes: supporting the Kigali Amendment to reduce HFCs, encouraging the development of affordable, sustainable alternatives, and educating colleagues about the environmental impact of medical devices (https://www.unep.org/ozonaction/who-we-are/about-montreal-protocol). Pharmaceutical companies are developing next-generation inhalers with propellants like vHFA-152a and hydrofluoroolefin-1234ze with much lower global warming potential (> 90% lower than current HFA formulations) (https://doi.org/10.1136/thorax-2022-BTSabstracts.66). While inhalers constitute a relatively small portion of overall greenhouse gas emissions compared to sectors like transportation and energy, we have both the opportunity and responsibility to mitigate climate change while continuing to provide appropriate care to our patients. Groups are being set up, such as the Inhaled Respiratory Medicine Innovation and Environmental Sustainability (IRIS) group (https://www.sustainable-respiratory-medicines.com/about-us) dedicated to advocating for the importance of inhaled respiratory medicines, continued access to these medicines, and preserving patient and physician choice of inhaler while promoting long-term environmental sustainability. By making thoughtful choices in our clinical practice and advocating for systemic change, we can contribute to a healthier planet for our patients while ensuring their respiratory needs are met with both clinical and environmental responsibility. The author declares no conflicts of interest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.288
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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