Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».