Small Airway Dysfunction in Cough Variant Asthma: Prevalence, Clinical, and Pathophysiological Features

Introduction: Small airway dysfunction (SAD) commonly presents in patients with classic asthma, which is associated with airway inflammation, disease severity, and asthma control. However, the prevalence of SAD, its relationship with cough severity and airway inflammation, and its development after antiasthmatic treatment in patients with cough variant asthma (CVA) need to be clarified. This study aimed to investigate the prevalence of SAD and its relationship with clinical and pathophysiological characteristics in patients with CVA and the change in small airway function after antiasthmatic treatment.Methods: We retrospectively analyzed 120 corticosteroid-naïve patients with CVA who had finished a standard questionnaire and relevant tests in a specialist cough clinic, such as cough visual analog scale (VAS), differential cells in induced sputum, fractional exhaled nitric oxide (FeNO) measurement, spirometry, and airway hyper-responsiveness. Information of 1-year follow-up was recorded in a part of patients who received complete cough relief after 2 months of treatment. SAD was defined as any two parameters of maximal mid-expiratory flow (MMEF)% pred, forced expiratory flow at 50% of forced vital capacity (FEF50%) pred, and forced expiratory flow at 75% of forced vital capacity (FEF75%) pred measuring <65%.Results: SAD occurred in 73 (60.8%) patients with CVA before treatment. The patients with SAD showed a significantly longer cough duration (24.0 vs. 6.0, p = 0.031), a higher proportion of women (78.1 vs. 59.6%, p = 0.029), older mean age (41.9 vs. 35.4, p = 0.005), and significantly lower forced expiratory volume in 1 s (FEV1%) pred, FEV1/FVC, MMEF% pred, FEF50% pred, FEF75% pred, PEF% pred, and PD20 (all p < 0.01) as compared with patients without SAD. There were no significant differences in cough VAS, sputum eosinophils count, FeNO, and TIgE level between patients with SAD and those without SAD. Among 105 patients who completed 2 months of antiasthmatic treatment and repeatedly experienced spirometry measurement, 57 (54.3%) patients still had SAD, despite a significant improvement in cough VAS, sputum eosinophils, FeNO, FEF50% pred, and PEF% pred (all p < 0.01). As compared with patients without SAD, patients with SAD showed no significant differences in the relapse rate (50.0 vs. 41.9%, p = 0.483) and wheeze development rate (10.4 vs. 0%, p = 0.063) during the follow-up.Conclusions: Small airway dysfunction occurred in over half of patients with CVA and persisted after short-term antiasthmatic treatment, which showed distinctive clinical and pathophysiological features.

Bullous Parametric Response Map for Functional Localization of COPD

Advanced bronchoscopic lung volume reduction treatment (BLVR) is now a routine care option for treating patients with severe emphysema. Patterns of low attenuation clusters indicating emphysema and functional small airway disease (fSAD) on paired CT, which may provide additional insights to the target selection of the segmental or subsegmental lobe of the treatments, require further investigation. The low attenuation clusters (LACS) were segmented to identify the scalar and spatial distribution of the lung destructions, in terms of 10 fractions scales of low attenuation density (LAD) located in upper lobes and lower lobes. The LACs of functional small airway disease (fSAD) were delineated by applying the technique of parametric response map (PRM) on the co-registered CT image data. Both emphysematous LACs of inspiratory CT and fSAD LACs on expiratory CT were used to derive the coefficients of the predictive model for estimating the airflow limitation. The voxel-wise severity is then predicted using the regional LACs on the co-registered CT to indicate the functional localization, namely, the bullous parametric response map (BPRM). A total of 100 subjects, 88 patients with mild to very severe COPD and 12 control participants with normal lung functions (FEV1/FVC % > 70%), were evaluated. Pearson’s correlations between FEV1/FVC% and LAV%HU-950 of severe emphysema are − 0.55 comparing to − 0.67 and − 0.62 of LAV%HU-856 of air-trapping and LAV%fSAD respectively. Pearson’s correlation between FEV1/FVC% and FEV1/FVC% predicted by the proposed model using LAD% of HU-950 and fSAD on BPRM is 0.82 (p < 0.01). The result of the Bullous Parametric Response Map (BPRM) is capable of identifying the less functional area of the lung, where the BLVR treatment is aimed at removing from a hyperinflated area of emphysematous regions.

Negative Ion Purifier Effects on Indoor Particulate Dosage to Small Airways

Indoor air quality is an important health factor as we spend more than 80% of our time indoors. The primary type of indoor pollutant is particulate matter, high levels of which increase respiratory disease risk. Therefore, air purifiers are a common choice for addressing indoor air pollution. Compared with traditional filtration purifiers, negative ion air purifiers (NIAPs) have gained popularity due to their energy efficiency and lack of noise. Although some studies have shown that negative ions may offset the cardiorespiratory benefits of air purifiers, the underlying mechanism is still unclear. In this study, we conducted a full-scale experiment using an in vitro airway model connected to a breathing simulator to mimic inhalation. The model was constructed using computed tomography scans of human airways and 3D-printing technology. We then quantified the effects of NIAPs on the administered dose of 0.5–2.5 μm particles in the small airway. Compared with the filtration purifier, the NIAP had a better dilution effect after a 1-h exposure and the cumulative administered dose to the small airway was reduced by 20%. In addition, increasing the negative ion concentration helped reduce the small airway exposure risk. NIAPs were found to be an energy-efficient air purification intervention that can effectively reduce the small airway particle exposure when a sufficient negative ion concentration is maintained.

Solid Fuel Exposure and Chronic Obstructive Pulmonary Disease in Never-Smokers

Background: Chronic obstructive pulmonary disease (COPD) is a public health challenge globally. The burden of COPD is high in never-smokers but little is known about its causes. We aimed to find the prevalence and correlates of COPD in never-smokers, with a special focus on solid fuel exposure.Methods: We conducted a cross-sectional study in Western China. COPD was defined by FEV1/FVC &lt; lower limits of normal (LLN). Descriptive statistics and multivariable logistic regression were used for analyses.Results: Six thousand two hundred and seventy one patients were enrolled between June 2015 and August 2016. The prevalence of COPD in never-smokers was 15.0% (95% confidence interval 14.1–15.9). The common independent predictors of COPD in never-smokers included age ≥60 years, exposure to solid fuel, living in a rural area and a history of tuberculosis. Participants with solid fuel exposure were 69% more likely to have COPD (adjusted odds ratio 1.69, 95% CI 1.41–2.04) than those without such exposure. In addition, we found a positive association between small airway dysfunction and solid fuel exposure (OR 1.35, 95% CI 1.18–1.53).Conclusions: This study confirmed the substantial burden of COPD among never-smokers and also defined the risk factors for COPD in never-smokers. Furthermore, we found a positive association between solid fuel exposure and COPD or small airway dysfunction.

Evaluation of Glucocorticoid Therapy in Asthma Children with Small Airway Obstruction Based on CT Features of Deep Learning

This study was aimed at exploring the treatment of asthma children with small airway obstruction in CT imaging features of deep learning and glucocorticoid. A total of 145 patients meeting the requirements in hospital were included in this study, and they were randomly assigned to receive aerosolized glucocorticoid ( n = 45 ), aerosolized glucocorticoid combined with bronchodilator ( n = 50 ), or oral steroids ( n = 50 ) for 4 weeks after discharge. The lung function and fractional exhaled nitric oxide (FENO) indexes of the three groups were measured, respectively, and then the effective rates were compared to evaluate the clinical efficacy of glucocorticoids with different administration methods and combined medications in the short-term maintenance treatment after acute exacerbation of asthma. Deep learning algorithm was used for CT image segmentation. The CT image is sent to the workbench for processing on the workbench, and then the convolution operation is performed on each input pixel point during the image processing. After 4 weeks of maintenance treatment, FEF50 %, FEF75 %, and MMEF75/25 increased significantly, and FENO decreased significantly ( P < 0.01 ). The improvement results of FEF50 %, FEF75 %, MMEF75/25, and FENO after maintenance treatment were as follows: the oral hormone group was the most effective, followed by the combined atomization inhalation group, and the hormone atomization inhalation group was the least effective. The differences among them were statistically significant ( P < 0.05 ). The accuracy of artificial intelligence segmentation algorithm was 81%. All the hormones were more effective than local medication in the treatment of small airway function and airway inflammation. In the treatment of aerosol inhalation, the hormone combined with bronchiectasis drug was the most effective in improving small airway obstruction and reducing airway inflammation compared with single drug inhalation. Deep learning CT images are simple, noninvasive, and intuitively observe lung changes in asthma with small airway functional obstruction. Asthma with small airway functional obstruction has high clinical diagnosis and evaluation value.

A Novel Non-invasive Method Allowing for Discovery of Pathologically Relevant Proteins From Small Airways

BackgroundThere is a lack of early and precise biomarkers for personalized respiratory medicine. Breath contains an aerosol of droplet particles, which are formed from the epithelial lining fluid when the small airways close and re-open during inhalation succeeding a full expiration. These particles can be collected by impaction using the PExA® method (Particles in Exhaled Air), and are derived from an area of high clinical interest previously difficult to access, making them a potential source of biomarkers reflecting pathological processes in the small airways.Research questionOur aim was to investigate if PExA method is useful for discovery of biomarkers that reflect pathology of small airways.Methods and analysis10 healthy controls and 20 subjects with asthma, of whom 10 with small airway involvement as indicated by a high lung clearance index (LCI ≥2.9 z-score), were examined in a cross-sectional design, using the PExA instrument. The samples were analysed with the SOMAscan proteomics platform (SomaLogic Inc). ResultsTwo hundred-seven proteins were detected in up to 80% of the samples. Nine proteins showed differential abundance in subjects with asthma and high LCI as compared to healthy controls. Two of these were less abundant (ALDOA4, C4), and seven more abundant (FIGF, SERPINA1, CD93, CCL18, F10, IgM, IL1RAP). sRAGE levels were lower in ex-smokers (n=14) than in never smokers (n=16). Gene Ontology (GO) annotation database analyses revealed that the PEx proteome is enriched in extracellular proteins associated with extracellular exosome-vesicles and innate immunity.ConclusionThe applied analytical method was reproducible and allowed identification of pathologically interesting proteins in PEx samples from asthmatic subjects with high LCI. The results suggest that PEx based proteomics is a novel and promising approach to study respiratory diseases with small airway involvement.