Introduction: Obesity is associated with severe asthma, but no specific treatment has been established. The gut microbiome is increasingly recognized as a crucial factor, but specific treatments focused on the gut microbiome have not been established. Recently, azithromycin has been found to have the capacity to attenuate exacerbations, a characteristic of severe asthma. The effect of azithromycin on obesity-induced severe asthma is not understood.
Methods: The purpose of the present study is to clarify the effect of azithromycin on exacerbations in asthmatic patients with obesity. To explore the mechanism, the gut microbiome, metabolites of microbes such as short-chain fatty acids, and blood inflammatory cytokines will be analyzed to evaluate the correlation with the effect of azithromycin on exacerbations in obesity-induced severe asthma. A multi-center, prospective, single-arm intervention study is planned.
Discussion: The present study will allow us to evaluate the effect of azithromycin on exacerbations, particularly in asthma patients with obesity, and explore biomarkers, targeting molecules including the gut microbiome, which are correlated with decreased exacerbations. The present results could contribute to identifying new therapeutic prospects and targeted microbes or molecules associated with severe clinical characteristics in asthmatic patients with obesity.
Trial Registration: This study has been registered as a prospective study with the University Hospital Medical Information Network (UMIN0000484389) and the Japan Registry of Clinical Trials (jRCTs071220023).
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http://dx.doi.org/10.3390/ijerph20031861 | DOI Listing |
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Respiratory Medicine Unit and NIHR Oxford Biomedical Research Centre, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
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Department of Chemical Sciences, College of Science and Information Technology, Tai Solarin, University of Education, Ijebu-Ode, Lagos, Ogun State, Nigeria.
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Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.
In this research, we propose analysis of -restricted censored time-to-event data via a -inflated beta regression ( -IBR) model. The outcome of interest is , where and are the time-to-event and follow-up duration, respectively. Our analysis goals include estimation and inference related to -restricted mean survival time ( -RMST) values and event-free probabilities at that address the censored nature of the data.
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