In asthma, treatment effectiveness is strongly influenced by the quality of inhaler use. New devices such as Spiromax® have been specifically developed to improve ease of use. It is crucial to determine whether switching to such a device improves inhaler technique and clinical outcomes, and to identify factors associated with handling errors. This observational study assessed inhaler device handling errors in 1435 asthma patients recruited via 135 participating physicians in France, before and after switching therapy from the Symbicort Turbuhaler® or Seretide® Diskus® to DuoResp® Spiromax®. Patients received training in the use of their new device at baseline and were re-assessed after three months. After three months of use, 67% of patients were using the DuoResp® Spiromax® with no handling errors, and 88% with no critical errors. The presence of comorbidities was associated with handling errors overall. Concurrent illness potentially affecting device handling and previous training were associated with critical device handling errors. Most patients (85.4%) preferred DuoResp® Spiromax® over their previous device. Levels of inadequately controlled or uncontrolled asthma were reduced from baseline among patients using DuoResp® Spiromax® (8.6% versus 64.6%), and were higher in patients with critical handling errors. Effective patient education, correct inhaler technique, treatment adherence and devices associated with high patient satisfaction are interrelated factors key to the successful delivery of inhaled asthma therapy. Inhaler technique and patient device satisfaction should be routinely assessed in treated patients with uncontrolled asthma. Supplemental data for this article can be accessed at publisher's website.
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http://dx.doi.org/10.1080/02770903.2021.1875482 | DOI Listing |
Int J Mol Sci
December 2024
Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, Zwirki i Wigury 101, 02-089 Warsaw, Poland.
Mass-spectrometry-based proteomics frequently utilizes label-free quantification strategies due to their cost-effectiveness, methodological simplicity, and capability to identify large numbers of proteins within a single analytical run. Despite these advantages, the prevalence of missing values (MV), which can impact up to 50% of the data matrix, poses a significant challenge by reducing the accuracy, reproducibility, and interpretability of the results. Consequently, effective handling of missing values is crucial for reliable quantitative analysis in proteomic studies.
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January 2025
Medical Big Data Research Center, Chinese PLA General Hospital, Beijing, China.
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View Article and Find Full Text PDFPhys Eng Sci Med
January 2025
Faculty of Engineering, Department of Biomedical Engineering, Universiti Malaya, Kuala Lumpur, Malaysia.
Personal Disord
January 2025
Faculte de psychologie et des sciences de l'education, Institut de recherche en sciences psychologiques, Universite catholique de Louvain.
Deficits of social cognition are regularly but inconsistently reported among individuals with antisocial personality disorder (ASPD). Because of the multifaceted nature of social cognition, deficits might be only observed when assessing specific facets of social cognition and under sufficiently demanding conditions. This study examined self-other distinction performance, a key facet lying at the core of the attachment-based model of mentalizing (Fonagy & Luyten, 2009).
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January 2025
Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida 32611, United States.
Reproducibility in untargeted metabolomics data processing remains a significant challenge due to software limitations and the complex series of steps required. To address these issues, we developed Nextflow4MS-DIAL, a reproducible workflow for liquid chromatography-mass spectrometry (LC-MS) metabolomics data processing, validated with publicly available data from MetaboLights (MTBLS733). Nextflow4MS-DIAL automates LC-MS data processing to minimize human errors from manual data handling.
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