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Purpose: Patients with severe asthma (SA) are at an increased risk of asthma-related hospitalizations and exacerbations. Despite concerns that COVID-19 circulation would increase exacerbations of SA, anecdotal reports suggest that social distancing and exposure avoidance may have led to reduced exacerbations. Patients and methods: CHRONICLE is an ongoing noninterventional observational study of 3100 subspecialist-treated patients with SA. Eligible adults (> 18 years of age) have (1) current use of monoclonal antibody (ie, biologic) therapy for SA, (2) use of maintenance systemic corticosteroids (mSCS) or other systemic immunosuppressants for > 50% of the prior 12 months for SA, or (3) persistently uncontrolled asthma while treated with high-dosage inhaled corticosteroids with additional controllers. For enrolled patients, electronic medical records were reviewed to record all exacerbations and asthma-related hospitalizations. Descriptive analyses were conducted of the monthly incidence of exacerbations, exacerbation-related visits to the emergency department (ED), and asthma hospitalizations from July 2018 through July 2021. Results: Exacerbations, exacerbation-related ED visits, and hospitalizations decreased since April 2020. Exacerbations in 2020 were 20% to 52% lower in April through August relative to the same months in 2019. Exacerbations remained lower than the prior year through May 2021. Similar results were observed by United States (US) census region, with an earlier decrease in exacerbation rates in the western US versus other regions. Across all months, exacerbation rates were lower among biologic recipients. Conclusion: In a clinical cohort of subspecialist-treated patients with SA, there was a meaningful reduction in exacerbations, exacerbation-related ED visits, and asthma hospitalizations following COVID-19-related stay-at-home orders and social distancing recommendations. Reasons for these reductions are likely multifactorial, including reduced viral infections due to less social contact and altered patient behavior. Keywords: management/control, healthcare resource use

The National Heart, Lung, and Blood Institute has sponsored several asthma clinical networks, but the Severe Asthma Research Program (SARP) is unique, because it is not a clinical trials network, and it includes both adults and children. Investigators in SARP have comprehensively characterized 1,644 patients with asthma over the past 10 years, including 583 individuals with severe asthma and 300 children below the age of 18 years. The diversity in clinical characteristics, physiologic measures, and biomarkers in a large number of subjects across the ages provides an ideal cohort in which to investigate asthma heterogeneity. Using both biased and unbiased approaches, multiple asthma phenotypes have been described in SARP. These phenotypic analyses have improved our understanding of heterogeneity in asthma, and may provide a starting point to transform clinical practice through the evidence-based classification of disease severity. Although these new phenotypes strive to make order out of a heterogeneous group of patients, they are limited by that heterogeneity. There may be large groups of patients, especially those with milder asthma, that can be grouped into a clinical phenotype to guide therapy, but there will always be patients on the “edge” of a phenotype who will not fit into these groupings. In the SARP cluster analysis, subjects on the “edge” of a phenotype frequently had lung function that was better or worse than other subjects in the same cluster, despite similar clinical characteristics. This suggests that different pathophysiologic mechanisms may be responsible for decrements in lung function in some subjects. This is extremely important for subjects with severe asthma who may be on the “edge” of two phenotypes that may be driven by different pathobiologic mechanisms that warrant different therapeutic approaches.

Mucus plugs occlude airways to obstruct airflow in asthma. Studies in patients and in mouse models show that mucus plugs occur in the context of type 2 inflammation, and studies in human airway epithelial cells (HAECs) show that IL-13-activated cells generate pathologic mucus independently of immune cells. To determine how HAECs autonomously generate pathologic mucus, we used a magnetic microwire rheometer to characterize the viscoelastic properties of mucus secreted under varying conditions. We found that normal HAEC mucus exhibited viscoelastic liquid behavior and that mucus secreted by IL-13-activated HAECs exhibited solid-like behavior caused by mucin cross-linking. In addition, IL-13-activated HAECs shows increased peroxidase activity in apical secretions, and an overlaid thiolated polymer (thiomer) solution shows an increase in solid behavior that was prevented by peroxidase inhibition. Furthermore, gene expression for thyroid peroxidase (TPO), but not lactoperoxidase (LPO), was increased in IL-13-activated HAECs and both TPO and LPO catalyze the formation of oxidant acids that cross-link thiomer solutions. Finally, gene expression for TPO in airway epithelial brushings was increased in patients with asthma with high airway mucus plug scores. Together, our results show that IL-13-activated HAECs autonomously generated pathologic mucus via peroxidase-mediated cross-linking of mucin polymers.

Approximately 5-10% of patients with asthma have severe disease. High-quality real-world studies are needed to identify areas for improved management. Aligned with the International Severe Asthma Registry, the CHRONICLE study (ClinicalTrials.gov: NCT03373045) was developed to address this need in the US. Learnings from prior studies were applied to develop a real-world, prospective, noninterventional study of US patients with confirmed severe asthma who are treated by subspecialist physicians and require biologic or maintenance systemic immunosuppressant therapy or who are uncontrolled by high-dosage inhaled corticosteroids and additional controllers. Target enrollment is 4000 patients, with patient observation for ≥3 years. A geographically diverse sample of allergist/immunologist and pulmonologist sites approach all eligible patients under their care and report patient characteristics, treatment, and health outcomes every 6 months. Patients complete online surveys every 1-6 months. From February 2018 to February 2019, 102 sites screened 1428 eligible patients; 936 patients enrolled. Study sites (40% allergist/immunologist, 42% pulmonologist, 18% both) were similar to other US asthma subspecialist samples. Enrolled patients were 67% female with median ages at enrollment and diagnosis of 55 (range: 18-89) and 26 (0-80) years, respectively. Median body mass index was 31 kg/m ; 3% and 29% were current or former smokers, respectively, and >60% reported ≥1 exacerbation in the prior year and suboptimal symptom control. CHRONICLE will provide high-quality provider- and patient-reported data from a large, real-world cohort of US adults with subspecialist-treated severe asthma.

Abstract Rationale Corticosteroids (CSs) are the most effective asthma therapy, but responses are heterogeneous and systemic CSs lead to long-term side effects. Therefore, an improved understanding of the contributing factors in CS responses could enhance precision management. Although several factors have been associated with CS responsiveness, no integrated/cluster approach has yet been undertaken to identify differential CS responses. Objectives To identify asthma subphenotypes with differential responses to CS treatment using an unsupervised multiview learning approach. Methods Multiple-kernel k-means clustering was applied to 100 clinical, physiological, inflammatory, and demographic variables from 346 adult participants with asthma in the Severe Asthma Research Program with paired (before and 2–3 weeks after triamcinolone administration) sputum data. Machine-learning techniques were used to select the top baseline variables that predicted cluster assignment for a new patient. Measurements and Main Results Multiple-kernel clustering revealed four clusters of individuals with asthma and different CS responses. Clusters 1 and 2 consisted of young, modestly CS-responsive individuals with allergic asthma and relatively normal lung function, separated by contrasting sputum neutrophil and macrophage percentages after CS treatment. The subjects in cluster 3 had late-onset asthma and low lung function, high baseline eosinophilia, and the greatest CS responsiveness. Cluster 4 consisted primarily of young, obese females with severe airflow limitation, little eosinophilic inflammation, and the least CS responsiveness. The top 12 baseline variables were identified, and the clusters were validated using an independent Severe Asthma Research Program test set. Conclusions Our machine learning–based approaches provide new insights into the mechanisms of CS responsiveness in asthma, with the potential to improve disease treatment.

Pediatric perioperative nurses are experiencing increased opportunities to participate in donations after cardiac death. An increased public awareness regarding transplantation has inspired more people to donate than in previous years. The demand for transplantable organs has led to opportunities that have increased donor candidates including living donors and cardiac death donors. Cardiac death in children is often sudden and unexpected, and is an emotional time not only for the family members but also for the hospital staff members, including perioperative nurses. However, when perioperative nurses adhere to standards and guidelines, they can perform their responsibilities in an ethical and compassionate manner and assist their team in doing so. This article reviews the guiding principles of pediatric organ donation after cardiac death, the phases of the process, and the ethical and moral issues surrounding donation.

Abstract Asthma is a heterogeneous disease with variable presentation and characteristics. There is a critical need to identify underlying molecular endotypes of asthma. We performed the largest transcriptomic analysis of 808 bronchial epithelial cell samples across 11 independent cohorts, including 3 cohorts from the Severe Asthma Research Program. Using seven datasets (218 patients with asthma, 148 healthy control subjects) as discovery cohorts, we identified 505 differentially expressed genes, which we validated in the remaining four datasets. Unsupervised clustering using the 505 differentially expressed genes identified four reproducible clusters of patients with asthma across all datasets, corresponding to healthy control subjects, patients with mild/moderate asthma, and patients with severe asthma with significant differences in several clinical markers of severity, including pulmonary function, Type 2 inflammation, fractional exhaled nitric oxide, and maximum bronchodilator reversibility. Importantly, we found the same clusters in pediatric patients using nasal lavage fluid cells, demonstrating the gene signature and clusters are not confounded by age and are conserved in both lower and upper airways. The four asthma clusters may represent a unifying framework for understanding the molecular heterogeneity of asthma. Further study could potentially enable a precision medicine approach of matching therapies with patients with asthma most likely to benefit.