Clinical and Experimental Allergy最新文献

Background: Asthma severity is influenced by complex immunologic and environmental factors. While allergic asthma is linked to increased susceptibility to respiratory infections, the combined role of allergy and antibiotic-treated infections in progression to severe asthma has not been fully evaluated.

Objective: To evaluate whether allergic asthma and recurrent respiratory infections (RRI) requiring antibiotics are associated with increased risk of developing severe asthma.

Methods: We conducted a registry-based cohort study using Swedish national registry data. Adults with mild-to-moderate asthma were identified in 2014 (baseline) based on prescription records and absence of severe disease indicators. During a two-year exposure window (2015-2016), RRI was defined as ≥ 2 antibiotic prescriptions for lower respiratory tract infections. The outcome was development of severe asthma during 2017-2019, based on ERS/ATS treatment criteria. Allergic asthma was defined by ≥ 2 prescriptions for anti-allergic medications at baseline.

Results: Among 113,393 patients, 24,692 (21.8%) had allergic asthma. RRI occurred more frequently in allergic versus non-allergic asthma (7.5% vs. 5.9%, p < 0.001). A total of 869 patients (0.77%) developed severe asthma. Incidence was higher in those with RRI and highest among patients with both allergic asthma and RRI (2.0%), corresponding to a relative risk of 3.47 (95% CI: 2.49-4.83) versus patients with neither exposure. Results were consistent after adjustment for age, sex and comorbidities.

Conclusion: Allergic asthma and antibiotic-treated respiratory infections were independent and additive predictors of severe asthma progression. These findings support a clinically actionable risk profile and may inform targeted preventive strategies in asthma management.

The cover image is based on the article Oesophageal Epithelial Cell-Intrinsic MHCII Regulates Food Antigen-Dependent Eosinophilic Esophagitis in an IFNγ-Dependent Manner by Eric M. Rodríguez-López et al., https://doi.org/10.1111/cea.70205.

Background: In China, therapeutic options are limited by the narrow availability of allergen preparations, with house dust mite (HDM) allergen immunotherapy (AIT) as the main choice for most patients. However, polysensitization is highly prevalent, and the benefit of HDM AIT in such patients remains uncertain. The study aims to evaluate the effectiveness of single-allergen HDM AIT on both perennial and coexisting allergen-specific symptoms in polysensitised allergic rhinitis (AR) patients and to explore predictors of treatment response.

Methods: We performed a multicenter retrospective cohort study including 81 patients with AR who were polysensitised to HDM and at least one other inhalant allergen (e.g., pollens, mould or animal dander). All participants received HDM subcutaneous immunotherapy (SCIT) for 12 to 36 months. Baseline characteristics, including serum allergen-specific IgE (sIgE) levels and comorbidities, were collected. Symptom severity was assessed using the Visual Analog Scale (VAS), and treatment response was defined as a ≥ 30% reduction in VAS scores from baseline. Statistical comparisons between responders and non-responders were conducted using Fisher's exact test for categorical variables and Mann-Whitney U tests for continuous data. Firth logistic regression was used to identify predictors of treatment response.

Results: The overall response rate for perennial symptoms was 68.8%, and varied in patients with co-existing allergies: 72.7% for moulds, 70.0% for animal dander, 65.5% for tree pollen, 70.2% for weed pollens. Allergen-specific symptom response rates varied across allergens: 68.2% for moulds, 30.0% for animal dander, 56.7% for tree pollens, 74.5% for weed pollens. Higher sIgE levels to HDM and mould were significantly associated with lower response rates in patients co-sensitised to both. A predictive model incorporating both sIgEs showed good specificity.

Conclusion: Single-allergen HDM AIT is effective in many polysensitised AR patients; however, its efficacy varies by coexisting allergen type and sIgE level. Patients co-sensitised to mould with high HDM and mould sIgE appeared to have poorer outcomes. These preliminary findings require confirmation in larger prospective studies to guide tailored AIT strategies.

Background: Mislabelled drug allergy (DA) remains a global public health challenge. A prior randomised trial (ADAPT) demonstrated that an intensive educational course improved DA knowledge and confidence among non-specialists. However, ADAPT was restricted to English-speaking participants and its generalisability remains unknown. To address this, a multinational implementation study expanding ADAPT (ADAPT-2) was performed.

Methods: Non-allergist physicians from Colombo (Sri Lanka), Guangzhou and Shenzhen (Mainland China), Hong Kong (Special Administrative Region of China) and Perth (Australia) completed a standardised DA educational course. In Mainland China, training was delivered via AI-assisted video localisation (converted into Mandarin while preserving the speaker's voice with lip-synced adaptation). DA knowledge, confidence and practice were assessed before and after completion. Subgroup analyses compared pre-post changes between Advanced Economies (AE: Australia, Hong Kong) and Emerging Economies (EE: Mainland China, Sri Lanka).

Results: Of 181 participants, overall baseline knowledge (53.5% ± 17.2%) and confidence (47.5% ± 22.7%) scores were suboptimal. EE participants had a lower knowledge level than AE (49.1% ± 15.5% vs. 70.1% ± 12.7%; p < 0.001). Following ADAPT-2, both knowledge (72.5% ± 16.0%, p < 0.001) and confidence (71.3% ± 17.5%, p < 0.001) scores significantly improved across all groups. ADAPT-2 delivered by AI-assisted video localisation was non-inferior to the English course in effectiveness (p > 0.05) and achieved high participant satisfaction (98.9% as 'somewhat clear' or better in clarity).

Conclusions: Deficits in DA knowledge persist widely among non-specialists, with marked disparities between AE and EE. ADAPT-2 bridged these gaps by universal improvements in both DA knowledge and confidence. AI-assisted training represents a scalable, equitable strategy for global implementation of standardised and evidence-based DA education.

Trial registration: ADAPT: NCT06399601.