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Background With the continued advancement of CFTR modulator therapies there is likely to be a burgeoning population of adult cystic fibrosis (CF) patients unable to expectorate sputum. Consequently, the detection and surveillance of pulmonary colonisation, previously reliant on sputum culture, needs re-examining. We hypothesised that cough swabs analysed with culture-independent analysis of the 16S gene could serve as a surrogate for colonisation of the lower airways. Methods Cough swabs and sputum samples were prospectively collected from consecutive adults and children with CF across two sites at regular outpatient appointments. Conventional culture analysis and next generation sequencing were used to compare paired same day samples. Results Twenty-two adults and 8 paediatric patients provided 75 paired cough swabs and sputum samples. Alpha diversity measures showed increased bacterial richness in sputum, while evenness and Simpson's diveristy index were higher in cough swabs. Within each sampling technique, microbial composition showed greater similarity when considering intra-patient variation. Poor concordance was observed between culture independent cough swabs and culture dependent/independent sputum analysis for specific pathogens, with cough swabs unable to accurately identify commonly associated CF pathogens (AUROCC range: 0.51 to 0.64). Conclusion Culture independent analysis of cough swabs provides an inaccurate diagnosis of lower respiratory tract colonisation and should not be used as a diagnostic test in patients with CF.

Acute respiratory distress syndrome (ARDS) is a heterogeneous clinical syndrome that manifests secondary to numerous etiologic insults, and consequently it is associated with a multitude of pathophysiological abnormalities. Despite more than 50 years of experimental studies, translation of these benchside discoveries into effective biological therapies has been elusive. In this review, some of the key advances made in our knowledge of the pathophysiology of ARDS, based on histopathology, imaging, protein, and transcriptomic biomarkers, are presented. Finally, the role of such human studies in understanding the pathophysiology of coronavirus disease 2019-related ARDS is reviewed.

Purpose To introduce the COVID-19 Reporting and Data System (CO-RADS) for standardized assessment of pulmonary involvement of COVID-19 on non-enhanced chest CT and report its initial interobserver agreement and performance. Methods The Dutch Radiological Society (NVvR) developed CO-RADS based on other efforts for standardization, such as Lung-RADS or BI-RADS. CO-RADS assesses the suspicion for pulmonary involvement of COVID-19 on a scale from 1 (very low) to 5 (very high). The system is meant to be used in patients presenting with moderate to severe symptoms of COVID-19. The system was evaluated using 105 chest CTs of patients admitted to the hospital with clinical suspicion of COVID-19 in whom RT-PCR was performed (62 +/- 16 years, 61 men, 53 with positive RT-PCR). Eight observers assessed the scans using CO-RADS. Fleiss’ kappa was calculated, and scores of individual observers were compared to the median of the remaining seven observers. The resulting area under the receiver operating characteristics curve (AUC) was compared to results from RT-PCR and clinical diagnosis of COVID-19. Results There was absolute agreement among observers in 573 (68.2%) of 840 observations. Fleiss’ kappa was 0.47 (95% confidence interval (CI) 0.45-0.47), with the highest kappa for CO-RADS categories 1 (0.58, 95% CI 0.54-0.62) and 5 (0.68, 95% CI 0.65-0.72). The average AUC was 0.91 (95% CI 0.85-0.97) for predicting RT-PCR outcome and 0.95 (95% CI 0.91-0.99) for clinical diagnosis. The false negative rate for CO-RADS 1 was 9/161 (5.6%, 95% CI 1.0-10%), and the false positive rate for CO-RADS 5 was 1/286 (0.3%, 95% CI 0-1.0%). Conclusions CO-RADS is a categorical assessment scheme for pulmonary involvement of COVID-19 on non-enhanced chest CT providing very good performance for predicting COVID-19 in patients with moderate to severe symptoms and has a substantial interobserver agreement, especially for categories 1 and 5.

Background: Detecting SARS-CoV-2 antibodies may help to diagnose COVID-19. Head-to-head validation of different types of immunoassays in well-characterized cohorts of hospitalized patients remains needed. Methods: We validated three chemiluminescence immunoassays (CLIAs) (Liaison, Elecsys, and Abbott) and one single molecule array assay (SIMOA) (Quanterix) for automated analyzers, one rapid immunoassay RIA (AllTest), and one ELISA (Wantai) in parallel in first samples from 126 PCR confirmed COVID-19 hospitalized patients and 158 pre-COVID-19 patients. Specificity of the AllTest was also tested in 106 patients with confirmed parasitic and dengue virus infections. Specificity of the Wantai assay was not tested due to limitations in sample volumes. Results: Overall sensitivity in first samples was 70.6 % for the Liaison, 71.4 % for the Elecsys, 75.4 % for the Abbott, 70.6 % for the Quanterix, 77.8 % for the AllTest, and 88.9 % for the Wantai assay, respectively. Sensitivity was between 77.4 % (Liaison) and 94.0 % (Wantai) after 10 dpso. No false positive results were observed for the Elecsys and Abbott assays. Specificity was 91.1 % for the Quanterix, 96.2 % for the Liaison, and 98.1 % for the AllTest assay, respectively. Conclusion: We conclude that low sensitivity of all immunoassays limits their use early after onset of illness in diagnosing COVID-19 in hospitalized patients. After 10 dpso, the Wantai ELISA has a relatively high sensitivity, followed by the point-of-care AllTest RIA that compares favorably with automated analyzer immunoassays.