Active clinical trials for "Asthma"

This is single-center cross-sectional mechanistic study in lean and obese children with moderate-severe asthma, followed by a randomized, SHAM-controlled trial of Inspiratory Training (IT). The primary outcome is to describe the contributions of inspiratory muscle dysfunction (IMD) and Small Airway Dysfunction (SAD) to obesity-related versus non-obesity-related asthma. The study will involve training (IT) for 8 weeks at three intensity levels (SHAM, low and high). Target dose: 150 inspirations three times weekly. The population includes 6 to 17-year-old children with moderate to severe asthma and with a body mass index qualifying as normal habitus (BMI 5th to 84th CDC percentile) or obese habitus (≥95th percentile BMI and less than 170% of the 95th CDC percentile). Participants will be involved for 10 weeks. The investigators will use analysis of covariance (ANCOVA) to estimate and test the difference in mean values of baseline measures between obese and non-obese cohorts. Covariates will include age, sex (male/female), race/ethnicity, baseline asthma severity (NAEPP step 2 vs ≥3), and atopy status

Around 1/3 of patients with COPD have elevated eosinophil levels. However, the role of eosinophils in COPD has not been yet understood and is probably different in COPD and in asthma. The aim of this study was to assess the expression of selected surface markers on eosinophils and to assess the gene expression in eosinophils in COPD and asthma patients. We are planning to enrol 12 COPD, 12 asthma and 12 control subjects. Patients will undergo routine clinical assessment, spirometry, blood sampling and sputum induction. Eosinophils will be isolated from blood and sputum. Surface markers on eosinophils will be assessed in flow cytometry, gene expression will be assessed by RNAseq.

Artificial intelligence (AI) offers substantial opportunities for healthcare, supporting better diagnosis, treatment, prevention and personalized care. Analysis of health images is one of the most promising fields for applying AI in healthcare, contributing to better prediction, diagnosis and treatment of diseases. Deep learning (DL) is currently one of the most powerful machine learning techniques. DL algorithms are able to learn from raw (or with little pre-processing) input data and build by themselves sophisticated abstract feature representations (useful patterns) that enable very accurate task decision making. Recently, DL has shown promising results in assisting lung disease analysis using computed tomography (CT) images. Current severe asthma guidelines recommend high-resolution and multidetector CT as a tool for disease evaluation. CT scans contain prognostic information, as the presence of bronchial wall thickening, air trapping, bronchial luminal narrowing, and bronchiectasis are associated with longer disease duration and disease severity in adults. Only a small number of studies have reported chest CT findings in children with severe asthma, and their relationship to clinical and pathobiological parameters yielded inconsistent results. Thus, to which extent CT scans add prognostic information beyond what can be inferred from clinical and biological data is still unresolved in children. The project is expected to build an DL-severity score to prognoses severe evolution for children with asthma, using a DL model to capture CT scan prognosis information.

Primary objective: - Describe the characteristics of enrolled severe asthma patients Secondary objectives: Assess the control of asthma under dupilumab (Dupixent®) treatment until 1 year Assess the clinical objectives of the asthma care Assess comorbidities associated with Type 2 inflammation Assess safety during the year of treatment

Asthma is the most common chronic condition among children and many children seek emergency department (ED) care. A key aspect of ED asthma management at the time of discharge is appropriate outpatient referral. Part of the challenge for ED providers is determining which patients require intensive outpatient support as ED providers often do not have the time or familiarity with the asthma guidelines to appropriately stratify asthma severity. Thus, the aim of this study is to determine whether the proportion of children referred to outpatient asthma care can be improved by incorporating a previously validated tool [the Pediatric Asthma Control and Communication Instrument for the Emergency Department (PACCI- ED)] into ED clinical care.

The purpose of this study is to characterize and compare the molecular gene expression profile in endobronchial biopsies and cells recovered in bronchial washings from study subjects who have asthma of varying disease severity and who are on maintenance inhaled corticosteroid (ICS) treatment, with that for healthy control subjects. These studies will produce transcriptomic profiles of gene expression associated with asthma disease severity. The investigators will also culture epithelial cells from study participant endobronchial brushings, including those with asthma of varying disease severity and healthy control subjects, to examine differences in the response to corticosteroids (CS) in vitro. These studies will test whether intrinsic differences exist between the responses to ICS in each group. 60 participants will be recruited with 15 of each mild, moderate and severe asthma as defined by the Global Initiative for Asthma (GINA) guidelines, as well as 15 healthy controls. Participants will undergo an initial visit to obtain informed consent, bloodwork and to assess asthma control using the Asthma Control Questionnaire (ACQ); if >1.5, ICS dose will be increased, as per GINA strategy, for a 2 week 'stabilization' phase. Repeat ACQ, spirometry and sputum induction will be performed at visit 2. Bronchoscopy will be performed at visit 3, 2-4 weeks after visit 2. Mucosal biopsies, bronchial brushings and bronchial washings will be performed and processed as per our prior methods. Mucosal biopsies will be homogenized and processed for RNA, or fixed for later sectioning and histological examination. Biopsy RNA will be assessed for quality and subjected to RNA-sequencing of all human genes (mRNA-seq). Bronchial washing cells will be collected for differential cell counting and mRNA-seq analysis. Bronchial epithelial cells (BECs) from the brushings will be cultured. BECs treated with CS and inflammatory cytokines will allow comparative assessment of BEC responses.

mINSPIRERS_RCT aims to assess the magnitude of the effect of a mobile app for improving asthma control in adolescents and adults with persistent asthma, followed at primary and secondary care in Portugal.

The goal of this exploratory and observational prospective study is to study the composition and phenotypes of blood leukocytes collected from asthmatic patients before and after instantiated treatment with the interleukin-5 neutralizing antibody mepolizumab. Comparisons will be made to leukocyte profiles in patients already on mepolizumab treatment, asthma patients without any biological treatment, and non-diseased control subjects.

GeoAsma is a study for the definition, validation and evaluation of predictive models on the influence of the environment on asthmatic patients in Andalusia.

Τherapeutic equivalence, randomized, multiple-dose, placebo-controlled, observer-blind, parallel group design consisting of a 2-week run-in period followed by a 4-week treatment period with Fluticasone propionate 100 mcg and Salmeterol 50 mcg inhalation powder/Respirent Pharmaceuticals (Test) or ADVAIR DISKUS® 100/50 mcg (Reference) or placebo.