We aimed to develop and validate a machine learning model using impulse oscillometry system (IOS) profiles for accurately classifying patients into three assessment-based categories: no airflow obstruction, asthma, and chronic obstructive pulmonary disease (COPD). Our research questions were as follows: (1) Can machine learning methods accurately classify obstructive disease states based solely on multidimensional IOS data? (2) Which IOS parameters and modeling algorithms provide the best discrimination? We used data for 480 patients (240 with COPD and 240 with asthma) and 84 healthy individuals for training. Physiological and IOS parameters were combined into six feature combinations. The classification algorithms tested were logistic regression, random forest, neural network, k-nearest neighbor, and support vector machine. The optimal feature combination for identifying individuals without pulmonary obstruction, with asthma, or with COPD included 15 IOS and physiological features. The neural network classifier achieved the highest accuracy (0.786). For discriminating between healthy and unhealthy individuals, two combinations of twenty-three features performed best in the neural network algorithm (accuracy of 0.929). When distinguishing COPD from asthma, the best combination included 15 features and the neural network algorithm achieved an accuracy of 0.854. This study provides compelling technical evidence and clinical justifications for advancing IOS data-driven models to aid in COPD and asthma management.

Purpose: Inadequate inhaler technique and nonadherence to therapy are associated with poorer clinical outcomes in chronic obstructive pulmonary disease (COPD). Shared decision-making (SDM), based on clinical evidence, patient goals and preferences, improves quality of care. This study aims to investigate the initial patients’ choices of inhaler devices in patients with newly-diagnosed COPD after an SDM process. Patients and Methods: We conducted a prospective, observational, multi-center study in four hospitals in Taiwan from December 2019 to July 2021. All treatment-naïve patients with newly-diagnosed COPD who were able to use three different inhalers of dual bronchodilators (Respimat^®, Ellipta^®, and Breezhaler^®) in the outpatient setting were enrolled. After an SDM process, every patient was prescribed with one inhaler chosen by him- or herself. Errors of using inhalers were recorded after prescription of the inhaler, and at the follow-up visit a month later. The patients’ adherence, satisfaction score, and willingness to keep the initially chosen inhaler were investigated. Results: In 109 enrolled patients, 43, 45, and 21 patients chose Respimat^®, Ellipta^®, and Breezhaler^®, respectively. Patients chose different inhalers had similar rates of critical error on both visits, while the rates greatly decrease on the follow-up visit, no matter which inhaler devices they chose initially. The majority of patients had good adherence (use as the prescription daily, n = 79, 82%), satisfaction (satisfaction score ≥ 4, n = 70, 73%), and strong willingness to keep the initial inhaler (n = 89, 93%) on the follow-up visit regardless of disease severity and their comorbidities. Conclusion: SDM might facilitate inhaler choosing, reduce inhaler errors (versus baseline) with good adherence, satisfaction and strong willingness to keep the initial inhaler in patients with newly-diagnosed COPD.

Idiopathic pulmonary fibrosis (IPF) may present comorbid obstructive lung diseases with small airway dysfunction (SAD). Existing guidelines suggest that inhaled bronchodilators should be used if the ratio of forced expiratory volume in the 1st second and forced vital capacity (FEV₁/FVC) < 0.7 in IPF. However, most IPF patients have FEV₁/FVC > 0.7 even with coexisting emphysema. We retrospectively enrolled IPF patients who were registered at our outpatient clinic. At baseline, 63 patients completed computed tomography (CT) scans, lung function measurements, and symptom questionnaires. Among these patients, 54 (85.71%) underwent antifibrotic treatment and 38 (60.32%) underwent long-acting bronchodilator treatment. The median FEV₁/FVC was 0.86. Not all patients treated with bronchodilators showed significant changes in lung function. IPF patients with SAD, determined by IOS parameters, showed significant improvement in FEV₁, FEF_25–75%, and symptom scores after bronchodilator treatment. Bronchodilator efficacy was not observed in patients without SAD. CT-confirmed emphysema was seen in 34.92% of patients. There were no changes in lung function or symptom scores after bronchodilator treatment in patients with emphysema. In conclusion, FEV₁/FVC cannot reflect the airflow limitation in IPF. Emphysema in IPF is not a deciding factor in whether patients should receive bronchodilator treatment. IOS parameters may be useful to guide bronchodilator therapy in patients with IPF coexisting with SAD.

SARS-CoV-2 spike proteins (SP) can bind to the human angiotensin-converting enzyme 2 (ACE2) in human pulmonary alveolar epithelial cells (HPAEpiC) and trigger an inflammatory process. Angiotensin-(1-7) may have an anti-inflammatory effect through activation of Mas receptor. This study aims to investigate whether SARS-CoV-2 SP can induce inflammation through ACE2 in the alveolar epithelial cells which can be modulated through angiotensin-(1-7)/Mas receptor axis. HPAEpiC were treated with SARS-CoV-2 SP in the presence or absence of ACE2 antagonist-dalbavancin and Mas receptor agonist-angiotensin-(1-7). Proinflammatory cytokine production (IL-6 and IL-8) were measured at mRNA and protein levels. MAP kinase phosphorylation and transcription factor activation was determined by Western Blot. Mas receptor was blocked by either antagonist (A779) or knockdown (specific SiRNA). Experiments were replicated using A549 cells. SARS-CoV-2 SP (5 μg/mL) significantly induced MAP kinase (ERK1/2) phosphorylation, downstream transcription factor (activator protein-1, AP-1) activation and cytokine production (IL-6 and IL-8) at both mRNA and protein levels. Pretreatment with dalbavancin (10 μg/mL), or angiotensin-(1-7) (10 μM) significantly reduced ERK1/2 phosphorylation, AP-1 activation, and cytokine production. However, these angiotensin-(1-7)-related protective effects were significantly abolished by blocking Mas receptor with either antagonist (A799,10 μM) or SiRNA knockdown. SARS-CoV-2 SP can induce proinflammatory cytokine production, which can be inhibited by either ACE2 antagonist or Mas receptor agonist-angiotensin-(1-7). Angiotensin-(1-7)-related protective effect on cytokine reduction can be abolished by blocking Mas receptor. Our findings suggest that ACE2/angiotensin-(1-7)/Mas axis may serve as a therapeutic target to control inflammatory response triggered by SARS-CoV-2 SP.

Purpose: Small airway dysfunction (SAD) is prevalent in asthma and chronic obstructive pulmonary disease (COPD). Aging is acknowledged to be associated with the loss of small airway structures. However, the impact of aging and pathophysiological changes on SAD in asthma and COPD remains unclear. We aimed to investigate the impact of aging and disease entity on pathophysiological change-related SAD in asthma and COPD assessed by spirometry and impulse oscillometry (IOS). Patients and Methods: We retrospectively reviewed adult patients diagnosed with asthma or COPD between May 2017 and August 2021 in Taipei Veterans General Hospital. Treatment-naïve COPD patients aged ≥ 60 years were enrolled, along with age- and gender-matched elderly asthmatics (EA), and younger asthmatics aged < 60 years (YA) for comparison. All participants underwent spirometry and IOS with a bronchodilator test. Blood eosinophil counts (BECs) and immunoglobulin E(IgE) levels were documented if blood tests were conducted at the time of diagnosis. Results: The mean age of YA, EA, and COPD were 44, 73, and 73 years, respectively. The FEV₁, FEV₁/FVC and FEF_25-75% were higher in the YA followed by EA and COPD groups. The spirometric values were significantly correlated with IOS parameters in both asthmatic and COPD groups. No significant differences were observed in baseline IOS parameters among the three groups for participants with FEV₁ ≥ 80% predicted. However, in patients with FEV₁< 80% predicted, COPD patients exhibited significantly worse spirometric values and most IOS parameters (except R₅-R₂₀) compared to asthmatics. Additionally, asthmatics with AX reduction ≥ 35% exhibited significantly higher levels of blood eosinophil counts and IgE. Conclusion: Aging process contributes to more impact on small airway reactance in asthma, while disease entity in COPD exhibits worse spirometric and IOS parameters compared to the age- and gender-matched EA.