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Expert statements concerning the tapering of oral corticosteroids (OCS) for the treatment of asthma

Health resource usage associated with the first year of mepolizumab

The primary objective of the CLIPPCAIR study is to construct and validate a new algorithm for predicting post-operative forced expiratory volume in 1 second (FEV1) values for lung resection candidates; this new model will be based on data derived from a thoracic CT scan with injection of contrast media. This registration includes information contained in the eCRF.

Determination of biomarkers to predict the response to treatment with dexamethasone for Sars-Cov(2 / COVID-19 pneumonia

The primary objective of the CLIPPCAIR study is to construct and validate a new algorithm for predicting post-operative forced expiratory volume in 1 second (FEV1) values for lung resection candidates; this new model will be based on data derived from a thoracic CT scan with injection of contrast media.

Determination of biomarkers to predict the response to treatment with dexamethasone for Sars-Cov(2 / COVID-19 pneumonia

eo-Delphi aims to create consensus for a core set of outcomes for the eo-Drive protocol using a modified Delphi method.

Determination of biomarkers to predict the response to treatment with dexamethasone for Sars-Cov(2 / COVID-19 pneumonia

The eo-Delphi project created consensus for priority outcomes for future research involving eosinophil-driven corticosteroid therapy in COPD populations.

Expert statements concerning the tapering of oral corticosteroids (OCS) for the treatment of asthma

Determination of biomarkers to predict the response to treatment with dexamethasone for Sars-Cov(2 / COVID-19 pneumonia

Health resource usage associated with the first year of mepolizumab

Standard patient training versus Vik chatbot guided training: a randomized controlled trial for asthma patients

Is AHI-CPAPflow really a surrogate for AHI-PSGgold?

Additional file 2: Table S1. Baseline FVC (mL) in subjects in the SENSCIS trial versus healthy reference subjects in subgroups by baseline characteristics.

Additional file 1: Figs. S1-S11. Supplementary Figure S1. Transduction of the HY03 hiPSC line with LF-ZsGreen particles allows transient ZsGreen expression and does not affect pluripotency. Supplementary Figure S2. LF-ZsGreen particles allow the highly efficient delivery of RNA in different hiPSC lines. Supplementary Figure S3. Characterization of the HY03-GFP non-clonal reporter hiPSC line. Supplementary Figure S4. NGS analysis of DNAH5 indel size distribution. Supplementary Figure S5. LentiFlash�� particle-based transduction of the CRISPR/Cas9 system to target the GFP fluorescent reporter sequence in a HCT116-GFP cell line that contains one GFP copy per cell. Supplementary Figure S6. Characterization of hiPSC clones in which DNAH5 or MCIDAS was knocked out by CRISPR/Cas9 gene editing using the LentiFlash�� system. Supplementary Figure S7. LentiFlash�� particle-based transduction of the CRISPR/Cas9 components to target specific genes results in high indel formation in different hiPSC lines. Supplementary Figure S8. Interallelic gene conversion following iPSC electroporation and following LentiFlash�� transduction of neural progenitors obtained from the PCD_02:30 hiPSC line results. Supplementary Figure S9. Characterization of hiPSC clonal lines harboring DNAH5 heterozygous mutations. Supplementary Figure S10. Specifically targeting the wild-type allele in hiPSC clones harboring a DNAH5 heterozygous mutation results in interallelic gene conversion. Supplementary Figure S11. Schematic representation of the expression cassettes carried by the plasmids used to produce the integrative lentiviral vector (ILV) that expresses the GFP reporter and of the expression cassettes carried by the plasmids used to produce non-integrative lentiviral particles (LentiFlash��) that express the ZsGreen reporter or the CRISPR/Cas9 systems. Supplementary Tables S1-3. Supplementary Table S1. sgRNA sequences. Supplementary Table S2. PCR primers. Supplementary Table S3. antibodies

The supplementary files contains detailed data mentionned in the main text on the standard rheometry results. The experiments limitations, the yield stress measurements and the non-linear (LAOS) measurements are described in details, as well as the response variability depending on the culture day. The micromanipulations performed with the optical tweezers are also detailed: The response dependance upon the probe size and materials is detailed, as well as the elastic moduli close to the interface. Fially, the mucus composition / rheology correlation can be evaluated on provided Figures, corresponding to the discussion in the main text.

Supplemental material, sj-docx-1-tar-10.1177_17534666221107313 for Oral corticosteroid-sparing effects of mepolizumab in severe eosinophilic asthma: evidence from randomized controlled trials and real-world studies by Thomas B. Casale, Autumn Burnette, Arnaud Bourdin, Peter Howarth, Beth Hahn, Alexandra Stach-Klysh and Sandhya Khurana in Therapeutic Advances in Respiratory Disease

Additional file 1. Technical Appendix.

Supplemental material, sj-docx-1-tar-10.1177_17534666221107313 for Oral corticosteroid-sparing effects of mepolizumab in severe eosinophilic asthma: evidence from randomized controlled trials and real-world studies by Thomas B. Casale, Autumn Burnette, Arnaud Bourdin, Peter Howarth, Beth Hahn, Alexandra Stach-Klysh and Sandhya Khurana in Therapeutic Advances in Respiratory Disease

Additional file 1: Appendix S1. Calculation of FVC (mL) in reference subjects.

Rationale: There is a need to minimize oral corticosteroid (OCS) use in patients with asthma to prevent their costly and burdensome adverse effects. Current guidelines do not provide recommendations for OCS tapering in patients with asthma.Objectives: To develop expert consensus on OCS tapering among international experts.Methods: A modified Delphi method was used to develop expert consensus statements relating to OCS use, tapering, adverse effects, adrenal insufficiency, and patient-physician shared decision-making. Initial statements proposed by experts were categorized, filtered for repetition, and presented back to experts over three ranking rounds to obtain consensus (≥70% agreement).Measurements and Main Results: One hundred thirty-one international experts participated in the study, and 296 statements were ranked. Numerous recommendations and guidance regarding appropriate OCS use were established. Experts agreed that OCS tapering should be attempted in all patients with asthma receiving maintenance OCS therapy, with personalization of tapering rhythm and speed. The importance of recognizing individual adverse effects was also established; however, a unified approach to the assessment of adrenal insufficiency was not reached. Shared decision-making was considered an important goal during the tapering process.Conclusions: In this Delphi study, expert consensus statements were generated on OCS use, tapering, adverse-effect screening, and shared decision-making, which may be used to inform clinical practice. Areas of nonconsensus were identified, highlighting uncertainty among the experts around some aspects of OCS use in asthma, such as adrenal insufficiency, which underscores the need for further research in these domains.

Introduction Discriminating asthma from chronic obstructive pulmonary disease (COPD) using medico-administrative databases is challenging but necessary for medico-economic analyses focusing on respiratory diseases. Artificial intelligence (AI) may improve dedicated algorithms. Objectives To assess performance of different AI-based approaches to distinguish asthmatics from COPD patients in medico-administrative databases where the clinical diagnosis is absent. An “Asthma COPD Overlap” category was defined to further test whether AI can detect complexity. Methods This study included 178,962 patients treated by two “R03” treatment prescriptions at least from January 2016 to December 2018 and managed by either a general practitioner and/or a pulmonologist participating in a permanent longitudinal observatory of prescription in ambulatory medicine (LPD). Clinical diagnoses are available in this database and were used as gold standards to develop diagnostic rules. Three types of AI approaches were explored using data restricted to demographics and treatment dispensations: multinomial regression, gradient boosting and recurrent neural networks (RNN). The best performing model (based on metric properties) was then applied to estimate the size of asthma and COPD populations based on a database (LRx) of treatment dispensations between July, 2018 and June, 2019. Results The best models were obtained with the boosting approach and RNN, with an overall accuracy of 68%. Performance metrics were better for asthma than COPD. Based on LRx data, the extrapolated numbers of patients treated for asthma and COPD in France were 3.7 and 1.2 million, respectively. Asthma patients were younger than COPD patients (mean, 49.9 vs. 72.1 years); COPD occurred mostly in men (68%) compared to asthma (33%). Conclusion AI can provide models with acceptable accuracy to distinguish between asthma, ACO and COPD in medico-administrative databases where the clinical diagnosis is absent. Deep learning and machine learning (RNN) had similar performances in this regard.

Additional file 7. Statistical analyses.

Additional file 4. Populations of patients depending on transformed manufacturer expressions of leaks.

Additional file 10. Univariate linear regression with patient-reported leak (0-10 VAS score) as the variable-of-interest.

Additional file 3. Device reported leak data.

Additional file 8. Distribution frequency of the Epworth Sleepiness Scale (ESS) scores. The dashed line corresponds to cumulative frequency.

Additional file 2: Supplemental Digital Content – Table 2. Definition of ICD-10 Codes.

Additional file 1. Methods.

Additional file 13. Visual Analogue Scales for mask related side-effect scores (0-10 score) according to the presence/absence of a bed partner.

Additional file 15. Summary of the three most recent and largest cohort studies (>500 patients) reporting mask related side-effects in CPAP-treated patients.

Additional file 3: Supplemental Digital Content – Table 3. PDs of patients in the groups derived from propensity scoring.