Recommendations for nurses and allied health professionals to help patients manage the cardio-renal impacts of climate change: findings from a systematic literature review
Notice bibliographique
Résumé
Abstract Background Climate change is associated with more frequent extreme weather events that impact human health. Extreme heat and cold, air pollution and wildfire smoke all affect individuals’ cardio-renal health. There is not only an urgent need to mitigate climate change, but also a growing need for interventions to protect the health of patients. As trusted frontline workers, nurses and allied health professionals are well positioned to do both. Purpose To identify published data on effective interventions that nurses and allied health professionals can use to help their patients adapt to and protect against the impacts of climate change on cardio-renal health. Methods We performed a systematic literature review in PubMed and Embase for all publications reporting climate change and cardio-renal health-related interventions up to June 2024, using the terms community, individual, healthcare professional, intervention, climate change, and cardio-renal. Studies reporting preventive measures and/or adaptive strategies, observational studies, real-world studies, clinical studies, and case series with ≥10 cases were included. Results The searches identified 16,912 eligible records in total. After removing duplicate records, the titles/abstracts of 12,239 records were screened. The full text of 128 records were reviewed, and results of 18 articles were summarised (Figure 1). The studies highlighted effective interventions covering various cooling and rehydration strategies, reducing exposure to air pollution, and ways to deal with heat-related illness [1 - 14]. Two articles provided tips on how to approach the topic of mitigating climate change and adapting to its effects when interacting with patients [15, 16]. These included using ‘health-related’ rather than ‘climate-related’ language and using communication materials with graphics and concise language to explain how climate change affects health conditions. Another two publications mentioned the limited knowledge of the impacts of climate change on patient outcomes amongst health professionals [17, 18]. Conclusion Nurses and allied health professionals can promote simple measures to protect the health of patients, e.g. cooling strategies, rehydration strategies, and reducing exposure to air pollution. However, since not all health professionals are familiar with the health impacts of climate change, they may not necessarily recommend these interventions. Effective communication and education can empower patients and colleagues to protect patient and planetary health. We encourage nurses and allied health professionals to find ways to keep up to date on the exponentially growing information on the health impacts of climate change and consider this in their professional work.Figure 1:PRISMA flow diagram
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 | 0,004 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 ».