Was wie Asthma anmutet, muss nicht (nur) Asthma sein…

Eine 40-jährige Nieraucherin wird wegen anhaltender Verschlechterung ihrer Asthmabeschwerden seit einer COVID-19 sechs Monate zuvor stationär aufgenommen. Seither besteht Arbeitsunfähigkeit. Die Asthmadiagnose ist seit frühester Kindheit bekannt, die Lungenfunktion sei schon immer eingeschränkt. Ein Puzzlespiel beginnt.

Predicting the effectiveness of high-flow oxygen therapy in COVID-19 patients: a single-centre observational study.

BACKGROUND: High-flow nasal cannula (HFNC) therapy is a helpful tool in the treatment of hypoxaemic respiratory failure. However, the clinical parameters predicting the effectiveness of HFNC in coronavirus-19 disease (COVID-19) patients remain unclear. METHODS: Sixteen COVID-19 patients undergoing HFNC in the Asklepios Lung Clinic Munich-Gauting, Germany between 16 March and 3 June 2020 were retrospectively included into the study. Seven patients successfully recovered after HFNC (Group 1), while 9 patients required intubation upon HFNC failure (Group 2). Relevant predictors for an effective HFNC therapy were analysed on day 0 and 4 after HFNC initiation via receiver operating characteristics. RESULTS: The groups did not differ significantly in terms of age, sex, body mass index, and comorbidities. Five patients died in Group 2 upon disease progression and HFNC failure. Group 1 required a lower oxygen supplementation (FiO2 0.46 [0.31-0.54] vs. 0.72 [0.54-0.76], P = 0.022) and displayed a higher PaO2/FiO2 ratio (115 [111-201] vs. 93.3 [67.2-145], P = 0.042) on day 0. In Group 2, fever persisted on day 4 (38.5 [38.0-39.4]°C vs. 36.5 [31.1-37.1]°C, P = 0.010). Serum C-reactive protein (CRP) levels > 108 mg L-1 (day 0) and persistent oxygen saturation < 89% and PaO2/FiO2 ratio < 91 (day 4) were identified as significant predictors for HFNC failure (area under curve 0.929, 0.933, and 0.893). CONCLUSIONS: Elevated oxygen saturation, decreased FiO2 and reduced serum CRP on day 4 significantly predict HFNC effectiveness in COVID-19 patients. Based on these parameters, larger prospective studies are necessary to further investigate the effectiveness of HFNC in the treatment of COVID-19-associated hypoxaemic respiratory failure.

Gender Differences in Health Care Workers' Risk-Benefit Trade-Offs for COVID-19 Vaccination.

BACKGROUND: Gender differences in vaccine acceptance among health care workers (HCWs) are well documented, but the extent to which these depend on occupational group membership is less well studied. We aimed to determine vaccine acceptance and reasons of hesitancy among HCWs of respiratory clinics in Germany with respect to gender and occupational group membership. METHODS: An online questionnaire for hospital staff of all professional groups was created to assess experiences with and attitudes towards COVID-19 and the available vaccines. Employees of five clinics were surveyed from 15 to 28 March 2021. RESULTS: 962 employees (565 [72%] female) took part in the survey. Overall vaccination acceptance was 72.8%. Nurses and physicians showed greater willingness to be vaccinated than members of other professions (72.8%, 84.5%, 65.8%, respectively; p = 0.006). In multivariate analyses, worries about COVID-19 late effects (odds ratio (OR) 2.86; p < 0.001) and affiliation with physicians (OR 2.20; p = 0.025) were independently associated with the willingness for vaccination, whereas age <35 years (OR 0.61; p = 0.022) and worries about late effects of vaccination (OR 0.13; p < 0.001) predicted vaccination hesitancy; no differences were seen with respect to gender. In separate analyses for men and women, only for men worries about COVID-19 late effects were relevant, while among women, age <35 years, worries about late effects of vaccination and worries about COVID-19 late effects played a role. CONCLUSIONS: There was no overall difference in vaccination acceptance between male and female HCWs, but there were gender-specific differences in the individual reasons on which this decision-making was based.

Automated quantitative thin slice volumetric low dose CT analysis predicts disease severity in COVID-19 patients.

PURPOSE: This study aimed to identify predictive (bio-)markers for COVID-19 severity derived from automated quantitative thin slice low dose volumetric CT analysis, clinical chemistry and lung function testing. METHODS: Seventy-four COVID-19 patients admitted between March 16th and June 3rd 2020 to the Asklepios Lung Clinic Munich-Gauting, Germany, were included in the study. Patients were categorized in a non-severe group including patients hospitalized on general wards only and in a severe group including patients requiring intensive care treatment. Fully automated quantification of CT scans was performed via IMBIO CT Lung Texture analysis™ software. Predictive biomarkers were assessed with receiver-operator-curve and likelihood analysis. RESULTS: Fifty-five patients (44% female) presented with non-severe COVID-19 and 19 patients (32% female) with severe disease. Five fatalities were reported in the severe group. Accurate automated CT analysis was possible with 61 CTs (82%). Disease severity was linked to lower residual normal lung (72.5% vs 87%, p = 0.003), increased ground glass opacities (GGO) (8% vs 5%, p = 0.031) and increased reticular pattern (8% vs 2%, p = 0.025). Disease severity was associated with advanced age (76 vs 59 years, p = 0.001) and elevated serum C-reactive protein (CRP, 92.2 vs 36.3 mg/L, p < 0.001), lactate dehydrogenase (LDH, 485 vs 268 IU/L, p < 0.001) and oxygen supplementation (p < 0.001) upon admission. Predictive risk factors for the development of severe COVID-19 were oxygen supplementation, LDH >313 IU/L, CRP >71 mg/L, <70% normal lung texture, >12.5% GGO and >4.5% reticular pattern. CONCLUSION: Automated low dose CT analysis upon admission might be a useful tool to predict COVID-19 severity in patients.