To determine the incidence and characteristics of superinfections in mechanically ventilated COVID-19 patients, and the impact of dexamethasone as standard therapy. This multicentre, observational, retrospective study included patients ≥ 18 years admitted from March 1st 2020 to January 31st 2021 with COVID-19 infection who received mechanical ventilation. Patient characteristics, clinical characteristics, therapy and survival were examined. 155/156 patients (115 men, mean age 62 years, range 26-84 years) were included. 67 patients (43%) had 90 superinfections, pneumonia dominated (78%). Superinfections were associated with receiving dexamethasone (66% vs 32%, p<0.0001), autoimmune disease (18% vs 5.7%, p<0.016) and with longer ICU stays (26 vs 17 days, p<0,001). Invasive fungal infections were reported exclusively in dexamethasone-treated patients [8/67 (12%) vs 0/88 (0%), p<0.0001]. Unadjusted 90-day survival did not differ between patients with or without superinfections (64% vs 73%, p=0.25), but was lower in patients receiving dexamethasone versus not (58% vs 78%, p=0.007). In multiple regression analysis, superinfection was associated with dexamethasone use [OR 3.7 (1.80–7.61), p<0.001], pre-existing autoimmune disease [OR 3.82 (1.13–12.9), p=0.031] and length of ICU stay [OR 1.05 p<0.001]. In critically ill COVID-19 patients, dexamethasone as standard of care was strongly and independently associated with superinfections.
Purpose: About 20–30% of patients with common variable immunodeficiency (CVID) develop granulomatous-lymphocytic interstitial lung disease (GLILD) as one of several non-infectious complications to their immunodeficiency. The purpose of this study was to identify biomarkers that could distinguish GLILD from other non-infectious complications in CVID. Methods: We analyzed serum biomarkers related to inflammation, pulmonary epithelium injury, fibrogenesis, and extracellular matrix (ECM) remodeling, and compared three subgroups of CVID: GLILD patients (n = 16), patients with other non-infectious complications (n = 37), and patients with infections only (n = 20). Results: We found that GLILD patients had higher levels of sCD25, sTIM-3, IFN-γ, and TNF, reflecting T cell activation and exhaustion, compared to both CVID patients with other inflammatory complications and CVID with infections only. GLILD patients also had higher levels of SP-D and CC16, proteins related to pulmonary epithelium injury, as well as the ECM remodeling marker MMP-7, than patients with other non-infectious complications. Conclusion: GLILD patients have elevated serum markers of T cell activation and exhaustion, pulmonary epithelium injury, and ECM remodeling, pointing to potentially important pathways in GLILD pathogenesis, novel targets for therapy, and promising biomarkers for clinical evaluation of these patients.
The aim of this study was to examine the burden of fungal disease in Norway, contributing to a worldwide effort to improve awareness of the needs for better diagnosis and treatment of such infections. We used national registers and actual data from the Departments of Microbiology from 2015 and estimated the incidence and/or prevalence of superficial, allergic and invasive fungal disease using published reports on specific populations at risk. One in 6 Norwegians suffered from fungal disease: Superficial skin infections (14.3%: 745,600) and recurrent vulvovaginal candidiasis in fertile women (6%: 43,123) were estimated to be the most frequent infections. Allergic fungal lung disease was estimated in 17,755 patients (341/100,000). Pneumocystis jirovecii was diagnosed in 262 patients (5/100,000), invasive candidiasis in 400 patients (7.7/100,000), invasive aspergillosis in 278 patients (5.3/100,000) and mucormycosis in 7 patients (0.1/100,000). Particular fungal infections from certain geographic areas were not observed. Overall, 1.79% of the population was estimated to be affected by serious fungal infections in Norway in 2015. Even though estimates for invasive infections are small, the gravity of such infections combined with expected demographic changes in the future emphasizes the need for better epidemiological data.