Setting: Whether and how cigarette smoking influences asthma are still matters of debate.
Objective: To identify risk factors associated with asthma according to whether individuals began active smoking before or after asthma onset.
Design: A sample of 544 individuals was examined using the protocol of the European Community Respiratory Health Status, Phase 1.
Results: Current active smoking (43.6%) was associated with wheezing during the past year (15.2%, OR 3.7; 95% CI 1.7-8.4), but not with asthma (17.6%, OR 0.78; 95% CI 0.48-1.26). However, active smoking modulated risk factors for asthma. Asthma that developed before smoking and asthma without smoking were both significantly related to nasal allergy, parental asthma and atopy (as assessed by skin prick test positivity and increased total and specific IgE levels). Only a lower FEV1 level was significantly associated with asthma that initiated after beginning smoking.
Conclusions: Our data put forward different phenotypes of asthma according to the timing of smoking onset and suggest that asthma either never accompanied by smoking or followed by smoking onset might be characterised by an allergic pattern. Longitudinal studies are warranted to further clarify the relationships among asthma phenotypes according to the sequence of disease onset and smoking.
Download full-text PDF |
Source |
---|
Immun Inflamm Dis
January 2025
Department of Medicine, Kilimanjaro Christian Medical University College, Moshi, Tanzania.
Introduction: Allergic rhinitis is the specific inflammation against allergen by immune defense cells on the nasal mucosa, which can lead to chronic nasal symptoms such as sneezing, itching, runny nose, and nasal congestion. It is associated with high morbidity including sinusitis, asthma, otitis media, hypertrophied inferior turbinate, and nasal polyps. Despite its complications, it remains poorly recognized and tracked.
View Article and Find Full Text PDFClin Exp Allergy
January 2025
School of Infection, Inflammation and Immunology, University of Birmingham, Brimingham, UK.
Data regarding Penicillin allergy labels (PALs) from India and Sri Lanka are sparse. Emerging data suggests that the proportion of patients declaring an unverified PAL in secondary care in India and Sri Lanka (1%-4%) is lesser than that reported in High Income Countries (15%-20%). However, even this relatively small percentage translates into a large absolute number, as this part of the world accounts for approximately 25% of the global population.
View Article and Find Full Text PDFAdv Healthc Mater
January 2025
Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China.
Eosinophils play a crucial role as effector cells in asthma pathogenesis, with their differentiation being tightly regulated by metabolic mechanisms. While the involvement of iron in various cellular processes is well known, its specific role in eosinophil differentiation has largely remained unexplored. This study demonstrates that iron levels are increased during the differentiation process from eosinophil progenitors to mature and activated eosinophils in the context of allergic airway inflammation.
View Article and Find Full Text PDFRespirology
January 2025
Division of Respiratory Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
Stat Med
February 2025
Department of Biostatistics and Health Data Science, University of Pittsburgh, Pittsburgh, Pennsylvania.
An important aspect of precision medicine focuses on characterizing diverse responses to treatment due to unique patient characteristics, also known as heterogeneous treatment effects (HTE) or individualized treatment effects (ITE), and identifying beneficial subgroups with enhanced treatment effects. Estimating HTE with right-censored data in observational studies remains challenging. In this paper, we propose a pseudo-ITE-based framework for analyzing HTE in survival data, which includes a group of meta-learners for estimating HTE, a variable importance metric for identifying predictive variables to HTE, and a data-adaptive procedure to select subgroups with enhanced treatment effects.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!