Pulmonary Ventilation

ObjectiveChronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease characterized by a persistent limitation in airflow. Gut microbiota is closely correlated with lung inflammation. However, gut microbiota has not been studied in patients with declining lung function, due to chronic lung disease progression.Subjects and methodsStool samples were obtained from 55 patients with COPD that were in stable condition at enrolment (stage 1) and at a 1-year follow-up (stage 2). After extracting stool DNA, we performed next generation sequencing to analyse the distribution of gut microbiota.ResultsPatients were divided to control and declining lung function groups, based on whether the rate of forced expiratory volume in 1 s (FEV1) had declined over time. An alpha diversity analysis of initial and follow-up stool samples showed a significant difference in the community richness of microbiota in the declining function group, but not in the control group. At the phylum level, Bacteroidetes was more abundant in the control group and Firmicutes was more abundant in the declining function group. The Alloprevotella genus was more abundant in the control group than in the declining function group. At 1-year follow-up, the mean proportions of Acinetobacter and Stenotrophomonas significantly increased in the control and declining function groups, respectively.ConclusionSome community shifts in gut microbiota were associated with lung function decline in COPD patients under regular treatment. Future studies should investigate the mechanism underlying alterations in lung function, due to changes in gut bacterial communities, in COPD.

BackgroundComorbidities can complicate the management of severe asthma; therefore, the presence of comorbid conditions or traits often need to be considered when considering treatment options for patients with severe asthma. The aim of this analysis is to investigate the efficacy of mepolizumab in patients with severe eosinophilic asthma and comorbidities.MethodsThis was a post hoc analysis (GSK ID:209140) of data from the Phase IIb/III studies DREAM, MENSA, SIRIUS, and MUSCA. Patients aged ≥ 12 years with severe eosinophilic asthma were randomized to: mepolizumab 750, 250, or 75 mg intravenously or placebo (DREAM); mepolizumab 75 mg intravenously or 100 mg subcutaneously or placebo (MENSA); or mepolizumab 100 mg subcutaneously or placebo (SIRIUS and MUSCA) every 4 weeks for 24 weeks in SIRIUS and MUSCA, 32 weeks in MENSA or 52 weeks in DREAM. In this analysis the primary endpoint was the annual rate of clinically significant exacerbations; secondary endpoints were Asthma Control Questionnaire-5 score, St George's Respiratory Questionnaire total score, and pre-bronchodilator forced expiratory volume in 1 s at study end. Subgroups were based on comorbidities at baseline.ResultsOverall, 1878 patients received placebo (n = 689) or mepolizumab (n = 1189). Across all comorbidity subgroups mepolizumab reduced the rate of clinically significant exacerbations by 44-68% versus placebo, improved Asthma Control Questionnaire-5 score by 0.27-0.59 points, and improved St George's Respiratory Questionnaire total score by 5.0-11.6 points. Pre-bronchodilator forced expiratory volume in 1 s was improved by 27.1-286.9 mL in all but one comorbidity subgroup, the diabetes mellitus subgroup.ConclusionsMepolizumab reduces exacerbations, and improves asthma control, health-related quality of life, and lung function in patients with severe eosinophilic asthma despite comorbid conditions, including upper respiratory conditions, psychopathologies, cardiovascular conditions, gastroesophageal reflux disease, diabetes mellitus, and obesity.Trial registrationhttps://clinicaltrials.gov/ DREAM, MEA112997/NCT01000506; MENSA, MEA115588/NCT01691521; SIRIUS, MEA115575/NCT01842607; MUSCA, 200862/NCT02281318.

The most appropriate physiological signals to develop simplified as well as accurate screening tests for obstructive sleep apnoea (OSA) remain unknown. This study aimed at assessing whether joint analysis of at-home oximetry and airflow recordings by means of machine-learning algorithms leads to a significant diagnostic performance increase compared to single-channel approaches. Consecutive patients showing moderate-to-high clinical suspicion of OSA were involved. The apnoea-hypopnoea index (AHI) from unsupervised polysomnography was the gold standard. Oximetry and airflow from at-home polysomnography were parameterised by means of 38 time, frequency, and non-linear variables. Complementarity between both signals was exhaustively inspected via automated feature selection. Regression support vector machines were used to estimate the AHI from single-channel and dual-channel approaches. A total of 239 patients successfully completed at-home polysomnography. The optimum joint model reached 0.93 (95%CI 0.90-0.95) intra-class correlation coefficient between estimated and actual AHI. Overall performance of the dual-channel approach (kappa: 0.71; 4-class accuracy: 81.3%) significantly outperformed individual oximetry (kappa: 0.61; 4-class accuracy: 75.0%) and airflow (kappa: 0.42; 4-class accuracy: 61.5%). According to our findings, oximetry alone was able to reach notably high accuracy, particularly to confirm severe cases of the disease. Nevertheless, oximetry and airflow showed high complementarity leading to a remarkable performance increase compared to single-channel approaches. Consequently, their joint analysis via machine learning enables accurate abbreviated screening of OSA at home.

Respiratory-swallowing coordination is critical for safe swallowing. Respiratory phase patterns, indicating the direction of respiration bracketing swallowing, appear minimally altered when oral airflow is measured alongside nasal airflow. Measures from an oronasal facemask also demonstrate broader features of swallowing non-respiratory flow (SNRF) associated with the respiratory-swallowing pause than previously reported. Additionally, nasal and oronasal flow estimates show variability in within-individual respiratory phase patterning. In this study, an oronasal facemask and separate nasal-only mask were used to assess healthy individuals, exploring how instrumentation influences respiratory phase pattern estimates across swallowing tasks. Characteristics of SNRF and variability of respiratory phase patterns were also investigated. Adding oral flow to nasal flow appeared to reduce estimated exhale-swallow-exhale patterning by 13% and increased the estimated frequency of alternative patterns, although this may include some genuine variance between the datasets due to asynchronous data acquisition from each mask. SNRF occurred in 87-97% of swallows, with inward and outward flow occurring at the onset and offset of the respiratory-swallowing pause. Test-retest reliability of respiratory phase patterns within individuals ranged from κ = 0.4 - 0.54, with ≥2 patterns observed across four trials >40% of the time. Findings suggest that adding oral to nasal flow alters estimates of respiratory phase patterns, particularly during ingestive swallowing tasks. SNRF is observed more frequently when measured through a closed system, presenting as inwardly- or outwardly-directed airflow at the beginning or end of the respiratory-swallowing pause. Finally, there appears to be considerable variability in respiratory phase patterning across trials of the same swallowing condition.