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BACKGROUND: Alterations in body composition, including a low fat-free mass index (FFMI), are common in patients with chronic obstructive pulmonary disease (COPD) and occur regardless of body weight.RESEARCH QUESTION: Is the impact of low FFMI on exercise capacity, health-related quality of life (HRQL) and systemic inflammation different among COPD patients stratified in different body mass index classifications?STUDY DESIGN AND METHODS: We analysed baseline data of COPD patients from the COSYCONET (COPD and Systemic Consequences - Comorbidities Network) cohort. Assessments included lung function, bioelectrical impedance analysis, six-minute walk distance (6MWD), HRQL and inflammatory markers. Patients were stratified in underweight (UW), normal weight (NW), pre-obese (PO) and obese (OB) according to BMI and as presenting low, normal or high FFMI using 25th and 75th percentiles of reference values. Linear mixed models were used to investigate the associations between FFM and fat mass with secondary outcomes in each BMI group.RESULTS: 2137 COPD patients (GOLD 1-4, 61% males, age: 65±8years, FEV1: 52.5±18.8%pred) were included. The proportions of patients in UW, NW, PO and OB groups were 12.3%, 31.3%, 39.6%, 16.8%. The frequency of low FFMI decreased from lower to higher BMI groups (UW:81%, NW:53%, PO:42%, OB:39%). FFM was associated with the 6MWD in the UW group, even when adjusting for a broad set of covariates (P<0.05). HRQL was not associated with FFM after adjustment for lung function or dyspnea (P>0.32). Fat mass was associated with higher systemic inflammation in the NW and PO groups (P<0.05).INTERPRETATION: In patients with COPD with lower weight, such as UW patients, higher FFMI is independently associated with better exercise capacity. In contrast, in PO and OB COPD patients, a higher FFMI were not consistently associated with better outcomes.

Peter Alter,1 Cosmina Stoleriu,2 Kathrin Kahnert,3,4 Markus Oliver Henke,5 Robert Bals,6 Franziska C Trudzinski,7 Henrik Watz,8 Tim Speicher,1 Sandra Söhler,1 Tobias Welte,9 Klaus F Rabe,10,11 Emiel FM Wouters,12,13 Claus F Vogelmeier,1 Rudolf A Jörres14 1Department of Medicine, Pulmonary, Critical Care and Sleep Medicine, Philipps University of Marburg (UMR), Member of the German Center for Lung Research (DZL), Marburg, Germany; 2Asklepios Lungenklinik Gauting, Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Gauting, Germany; 3Department of Medicine V, LMU University Hospital, LMU Munich, Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany; 4MediCenterGermering, Germering, Germany; 5Klinik für Innere Medizin und Pneumologie, Krankenhaus Martha-Maria, Munich, Germany; 6Department of Internal Medicine V, Pulmonology, Allergology, Intensive Care Medicine, Saarland University Hospital, Homburg, Germany; 7Department of Pneumology and Critical Care Medicine, Thoraxklinik, University of Heidelberg, Translational Lung Research Center Heidelberg (TLRC-H), Member of the Center for Lung Research (DZL), Heidelberg, Germany; 8Pulmonary Research Institute at LungenClinic Grosshansdorf, Airway Research Center North (ARCN), Member of the German Center for Lung Research (DZL), Grosshansdorf, Germany; 9Clinic for Pneumology, Hannover Medical School, Member of the German Center for Lung Research (DZL), Hannover, Germany; 10LungenClinic Grosshansdorf, Airway Research Center North (ARCN), Member of the German Center for Lung Research (DZL), Grosshansdorf, Germany; 11Department of Medicine, Christian-Albrechts-University, Kiel, Germany; 12Department of Respiratory Medicine, Maastricht University Medical Centre, Maastricht, Netherlands; 13Ludwig Boltzmann Institute for Lung Health, Vienna, Austria; 14Institute and Outpatient Clinic for Occupational, Social and Environm

Laidlaw TM, Menzies-Gow A, Caveney S, et al. J Asthma Allergy. 2023;16:915–932. The authors have advised there is an error in Figure 1 on page 922. The n= x-axis data were transposed for the treatment groups for both the Patients with NPs and Patients without NPs. The correct Figure 1 is as follows. Figure 1 AAER over 52 weeks in patients with or without nasal polyps in the 2 years before randomization in the NAVIGATOR study.Abbreviations: AAER, annualized asthma exacerbation rate; CI, confidence interval; NP, nasal polyp; Q4W, every 4 weeks.Note: n, number of patients contributing to the analysis. The authors apologize for this error.

Tanya M Laidlaw1,2 &ast;, Andrew Menzies-Gow3 &ast;, Scott Caveney,4 Joseph K Han,5 Nicole Martin,6,7 Elliot Israel,8 Jason K Lee,9,10 Jean-Pierre Llanos,11 Neil Martin,12,13 Ayman Megally,14 Bhavini Parikh,14 Sylvia Vong,15 Tobias Welte,16 Jonathan Corren17 1Jeff and Penny Vinik Center for Allergic Diseases Research, Division of Allergy and Clinical Immunology, Brigham and Women’s Hospital, Boston, MA, USA; 2Department of Medicine, Harvard Medical School, Boston, MA, USA; 3Royal Brompton and Harefield Hospitals, School of Immunology and Microbial Sciences, King’s College London, London, UK; 4Global Development, Inflammation, R&D, Amgen, Thousand Oaks, CA, USA; 5Department of Otolaryngology, Head and Neck Surgery, Eastern Virginia Medical School, Norfolk, VA, USA; 6Biometrics, Late-Stage Development, Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA; 7Cytel Inc, Waltham, MA, USA; 8Divisions of Pulmonary and Critical Care Medicine and Allergy and Clinical Immunology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA; 9Evidence Based Medical Educator Inc., Toronto, ON, Canada; 10Toronto Allergy and Asthma Clinic, Toronto, ON, Canada; 11Global Medical Affairs, Amgen, Thousand Oaks, CA, USA; 12Respiratory and Immunology, BioPharmaceuticals Medical, AstraZeneca, Cambridge, UK; 13University of Leicester, Leicester, UK; 14Late-Stage Development, Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA; 15Translational Science and Experimental Medicine, Early Respiratory and Immunology, AstraZeneca, Gaithersburg, MD, USA; 16Department of Respiratory Medicine and German Center for Lung Research, Hannover Medical School, Hannover, Germany; 17David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, USA&ast;These authors contributed equally to this workCorrespondence: Tanya M Laidlaw, Jeff and Penny Vinik Center for Allergic

Pia Maria Plank,1,&ast; Christopher Alexander Hinze,2,&ast; Victoria Campbell,3 Stefanie Konwert,4 Tobias Welte,1,4 Nora Drick,1 Moritz Z Kayser,1 Hendrik Suhling,1,4,&ast; Jan Fuge1,4,&ast; 1Department of Cardiology and Angiology, Hannover Medical School, Hannover, Germany; 2Department of Respiratory Medicine and Infectious Disease, Hannover Medical School, Hannover, Germany; 3Department of Paediatric Pulmonology, Allergology and Neonatology, Hannover Medical School, Hannover, Germany; 4Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), German Center for Lung Research (DZL), Hannover, Germany&ast;These authors contributed equally to this workCorrespondence: Christopher Alexander Hinze, Department of Respiratory Medicine and Infectious Disease, Hannover Medical School, Carl-Neuberg-Str. 1, Hannover, 30625, Germany, Tel +49 511-5323531, Email hinze.christopher@mh-hannover.dePurpose: Asthma is associated with a high prevalence of psychopathological disorders, especially depressive disorders or anxiety. In patients with uncontrolled severe asthma, monoclonal antibody (mAb)-therapy positively influenced control of mental disorders. Therefore, we evaluated the impact of antibody therapy on the burden of these mental diseases depending on responder status.Patients and Methods: Data were collected retrospectively in patients with uncontrolled severe asthma (n = 82) prior to mAb-therapy (“baseline”) (omalizumab, dupilumab, benralizumab or mepolizumab). Symptoms of Major Depressive Disorder (MDD) or General Anxiety Disorder (GAD) were detected at baseline using the Hospital Anxiety and Depression Scale (HADS), as well as general sociodemographic data and lung function parameters. At 6-month (± 3 month) follow-up, the burden of psychopathological symptoms under mAb-therapy was assessed using the Patient Health Questionnaire-2 (PHQ-2) and Generalized Anxiety Disorder Scale-2 (GAD-2). Response status was classified using the

S100A8/A9 has important immunomodulatory roles in antibacterial defense, but its relevance in focal pneumonia caused by Streptococcus pneumoniae (S. pneumoniae) is understudied. We show that S100A9 was significantly increased in BAL fluids of patients with bacterial but not viral pneumonia and correlated with procalcitonin and sequential organ failure assessment scores. Mice deficient in S100A9 exhibited drastically elevated Zn$^{2+}$ levels in lungs, which led to bacterial outgrowth and significantly reduced survival. In addition, reduced survival of S100A9 KO mice was characterized by excessive release of neutrophil elastase, which resulted in degradation of opsonophagocytically important collectins surfactant proteins A and D. All of these features were attenuated in S. pneumoniae-challenged chimeric WT→S100A9 KO mice. Similarly, therapy of S. pneumoniae-infected S100A9 KO mice with a mutant S100A8/A9 protein showing increased half-life significantly decreased lung bacterial loads and lung injury. Collectively, S100A9 controls central antibacterial immune mechanisms of the lung with essential relevance to survival of pneumococcal pneumonia. Moreover, S100A9 appears to be a promising biomarker to distinguish patients with bacterial from those with viral pneumonia. Trial registration: Clinical Trials register (DRKS00000620).

Background Optimal anticoagulation strategies for COVID-19 patients with the acute respiratory distress syndrome (ARDS) on venovenous extracorporeal membrane oxygenation (VV ECMO) remain uncertain. A higher incidence of intracerebral hemorrhage (ICH) during VV ECMO support compared to non-COVID-19 viral ARDS patients has been reported, with increased bleeding rates in COVID-19 attributed to both intensified anticoagulation and a disease-specific endotheliopathy. We hypothesized that lower intensity of anticoagulation during VV ECMO would be associated with a lower risk of ICH. In a retrospective, multicenter study from three academic tertiary intensive care units, we included patients with confirmed COVID-19 ARDS requiring VV ECMO support from March 2020 to January 2022. Patients were grouped by anticoagulation exposure into higher intensity, targeting anti-factor Xa activity (anti-Xa) of 0.3–0.4 U/mL, versus lower intensity, targeting anti-Xa 0.15–0.3 U/mL, cohorts. Mean daily doses of unfractionated heparin (UFH) per kg bodyweight and effectively measured daily anti-factor Xa activities were compared between the groups over the first 7 days on ECMO support. The primary outcome was the rate of ICH during VV ECMO support. Results 141 critically ill COVID-19 patients were included in the study. Patients with lower anticoagulation targets had consistently lower anti-Xa activity values over the first 7 ECMO days (p < 0.001). ICH incidence was lower in patients in the lower anti-Xa group: 4 (8%) vs 32 (34%) events. Accounting for death as a competing event, the adjusted subhazard ratio for the occurrence of ICH was 0.295 (97.5% CI 0.1–0.9, p = 0.044) for the lower anti-Xa compared to the higher anti-Xa group. 90-day ICU survival was higher in patients in the lower anti-Xa group, and ICH was the strongest risk factor associated with mortality (odds ratio [OR] 6.8 [CI 2.1–22.1], p = 0.001). Conclusions For COVID-19 patients on VV ECMO support anticoagulated with heparin

Background: Coronavirus-associated acute respiratory distress syndrome (CARDS) has limited effective therapy to date. NLRP3 inflammasome activation induced by SARS-CoV-2 in COVID-19 contributes to cytokine storm. Methods: This randomised, multinational study enrolled hospitalised patients (18–80 years) with COVID-19-associated pneumonia and impaired respiratory function. Eligible patients were randomised (1:1) via Interactive Response Technology to DFV890 + standard-of-care (SoC) or SoC alone for 14 days. Primary endpoint was APACHE II score at Day 14 or on day-of-discharge (whichever-came-first) with worst-case imputation for death. Other key assessments included clinical status, CRP levels, SARS-CoV-2 detection, other inflammatory markers, in-hospital outcomes, and safety. Findings: Between May 27, 2020 and December 24, 2020, 143 patients (31 clinical sites, 12 countries) were randomly assigned to DFV890 + SoC (n = 71) or SoC alone (n = 72). Primary endpoint to establish clinical efficacy of DFV890 vs. SoC, based on combined APACHE II score, was not met; LSM (SE), 8·7 (1.06) vs. 8·6 (1.05); p = 0.467. More patients treated with DFV890 vs. SoC showed ≥ 1-level improvement in clinical status (84.3% vs. 73.6% at Day 14), earlier clearance of SARS-CoV-2 (76.4% vs. 57.4% at Day 7), and mechanical ventilation-free survival (85.7% vs. 80.6% through Day 28), and there were fewer fatal events in DFV890 group (8.6% vs. 11.1% through Day 28). DFV890 was well tolerated with no unexpected safety signals. Interpretation: DFV890 did not meet statistical significance for superiority vs. SoC in primary endpoint of combined APACHE II score at Day 14. However, early SARS-CoV-2 clearance, improved clinical status and in-hospital outcomes, and fewer fatal events occurred with DFV890 vs. SoC, and it may be considered as a protective therapy for CARDS. Trial registration: ClinicalTrials.gov, NCT04382053.