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Enregistrement W4408499533 · doi:10.2147/copd.s498088

COPD Exacerbations, Air Pollutant Fluctuations, and Individual-Level Factors in the Pandemic Era

2025· article· en· W4408499533 sur OpenAlexafffundabout
Sahar Mikaeeli, Dany Doiron, Jean Bourbeau, Pei Zhi Li, Shawn D. Aaron, Kenneth R. Chapman, Paul Hernandez, François Maltais, Darcy D. Marciniuk, Denis E. O’Donnell, Don D. Sin, Brandie Walker, Wan C. Tan, Simon Rousseau, Bryan Ross

Notice bibliographique

RevueInternational Journal of COPD · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Obstructive Pulmonary Disease (COPD) Research
Établissements canadiensUniversity of CalgarySt. Paul's HospitalUniversity of British ColumbiaQueen's UniversityUniversity of SaskatchewanUniversité LavalInstitut universitaire de cardiologie et de pneumologie de QuébecDalhousie UniversityToronto General HospitalUniversity of TorontoOttawa HospitalUniversity of OttawaMcGill University Health Centre
Organismes subventionnairesFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchGlaxoSmithKlineGovernment of CanadaMcGill University Health CentreMcGill UniversityUniversity of OttawaUniversity of TorontoDalhousie UniversityReseau canadien de recherche respiratoireAstraZeneca CanadaQueen's UniversityJohns Hopkins UniversityAstraZeneca
Mots-clésCOPDPandemicCoronavirus disease 2019 (COVID-19)Air pollutantsPollutantMedicineEnvironmental healthEnvironmental scienceAir pollutionInternal medicineDiseaseChemistryInfectious disease (medical specialty)

Résumé

récupéré en direct d'OpenAlex

Purpose: Pandemic-era associations between air pollutant exposures and exacerbations of chronic obstructive pulmonary disease (COPD) are under-explored. Given the considerable observed pandemic-era pollutant fluctuations, these associations were investigated along with possible individual-level risk factors. Patients and Methods: Participants with spirometry-confirmed COPD from Canadian Cohort Obstructive Lung Disease (CanCOLD) were included, with data collected before (“pre-pandemic”) and during (“pandemic”) the COVID-19 pandemic. Nitrogen dioxide (NO 2 ), fine particulate matter (PM 2.5 ), ground-level ozone (O 3 ), total oxidant (O x ) and weather data were obtained from national databases. Associations between each air pollutant and “symptom-based” exacerbations (increased dyspnea or sputum volume/purulence ≥ 48hrs) and “event-based” exacerbations (“symptom-based” plus requiring antibiotics, corticosteroids, or unscheduled healthcare use) were estimated in separate models. Generalized estimating equations (GEE) models were reported as rate ratios (RRs) per interquartile range (IQR) increment in pollutant concentration with 95% confidence intervals (95% CIs). Results: NO 2 , PM 2.5 , and O x (NO 2 +O 3 ) concentrations (but not O 3 ) fell significantly during the pandemic. In the 673 participants with COPD included, both symptom-based and event-based exacerbation rates were likewise significantly higher during the pre-pandemic period. During the pre-pandemic period, O x was positively associated with symptom-based exacerbations (RR: 1.21 [1.08,1.36]). During the pandemic period, O x was positively associated with symptom-based (1.46 [1.13,1.89]) and event-based (1.43 [1.00,2.05]) exacerbations. Fewer self-reported pandemic protective behaviors, and higher viral infectious symptoms, were also associated with exacerbations. In stepwise multivariable risk-factor analyses, female gender (1.23 [1.04,1.45] and 1.41 [1.13,1.76]) and co-morbid asthma (1.65 [1.34,2.03] and 1.54 [1.19,2.00]) were associated with symptom-based and event-based exacerbations, respectively, blood eosinophils (1.42 [1.10,1.84]) were associated with event-based exacerbations, and each IQR increment in O x was associated with symptom-based exacerbations (1.31 [1.06,1.61]). Conclusion: O x exposure was consistently associated with symptom-based COPD exacerbations, and female gender, co-morbid asthma, and blood eosinophilia were found to be relevant risk factors. Plain Language Summary: Previous research has identified air pollution as a relevant non-infectious trigger for episodic ‘lung attacks’, referred to as exacerbations, in patients living with chronic obstructive pulmonary disease (COPD). Very few studies, however, have studied this relationship during the COVID-19 pandemic. During that time, there were large fluctuations in key forms of air pollution (air pollutants). The few studies available used population-level approaches and relied on hospital administrative coding of visits to classify the disease and to identify exacerbation events. This approach may lead to potentially missing clinically important non-severe events and may limit individual-level risk factor assessment around this period. This study was conducted in participants with COPD as confirmed by the gold-standard test, spirometry, who were living in 9 Canadian cities across 6 provinces. The results showed that while the air pollutants nitrogen dioxide (NO 2 ), fine particulate matter (PM 2.5 ), and total oxidant (O x ) concentrations were all notably higher before the pandemic (pre-pandemic), only ambient O x concentration was consistently associated with exacerbations. This relationship was seen across both pre-pandemic and pandemic periods. Female gender, co-morbid asthma, and eosinophilia were identified as notable risk factors for exacerbations and were effect modifiers for the association between O x exposure and exacerbations. This study adds to a very limited existing literature on the relationship between air pollutant fluctuations and exacerbations of COPD around the pandemic era and highlights important risk factors to guide targeted public health and exposure response interventions. Keywords: Chronic obstructive pulmonary disease, acute exacerbations of chronic obstructive pulmonary disease, ambient air pollution, COVID-19 pandemic, total oxidant concentration

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,064
Score d'incertitude au seuil0,395

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,040
Tête enseignante GPT0,342
Écart entre enseignants0,301 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2025
Routes d'admission3
Résumé présentoui

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