Low frequency of community-acquired bacterial co-infection in patients hospitalized for COVID-19 based on clinical, radiological and microbiological criteria; a retrospective cohort study.

BackgroundTo define the frequency of respiratory community-acquired bacterial co-infection in patients with coronavirus disease 2019 (COVID-19) based on a complete clinical assessment, including prior antibiotic use, clinical characteristics, inflammatory markers, chest computed tomography (CT) results and microbiological test results. MethodsThis study was conducted within a cohort of prospectively included patients admitted for COVID-19 in our tertiary medical centres between 1-3-2020 and 1-6-2020. A multidisciplinary study team developed a diagnostic protocol to retrospectively categorize patients as unlikely, possible or probable bacterial co-infection based on clinical, radiological and microbiological parameters in the first 72 hours of admission. Within the three categories, we summarized patient characteristics and antibiotic consumption. ResultsAmong 281 included COVID-19 patients, bacterial co-infection was classified as unlikely in 233 patients (82.9%), possible in 35 patients (12.4%) and probable in 3 patients (1.1%). Ten patients (3.6%) could not be classified due to inconclusive data. Within 72 hours of hospital admission, 81% of the total study population and 78% of patients classified as unlikely bacterial co-infection received antibiotics. ConclusionsCOVID-19 patients are unlikely to have a respiratory community-acquired bacterial co-infection. Prospective studies should define the safety of restrictive antibiotic use in COVID-19 patients.

Performance of Kiestra Total Laboratory Automation Combined with MS in Clinical Microbiology Practice

BACKGROUND: Microbiological laboratories seek technologically innovative solutions to cope with large numbers of samples and limited personnel and financial resources. One platform that has recently become available is the Kiestra Total Laboratory Automation (TLA) system (BD Kiestra B.V., the Netherlands). This fully automated sample processing system, equipped with digital imaging technology, allows superior detection of microbial growth. Combining this approach with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MS) (Bruker Daltonik, Germany) is expected to enable more rapid identification of pathogens. METHODS: Early growth detection by digital imaging using Kiestra TLA combined with MS was compared to conventional methods (CM) of detection. Accuracy and time taken for microbial identification were evaluated for the two methods in 219 clinical blood culture isolates. The possible clinical impact of earlier microbial identification was assessed according to antibiotic treatment prescription. RESULTS: Pathogen identification using Kiestra TLA combined with MS resulted in a 30.6 hr time gain per isolate compared to CM. Pathogens were successfully identified in 98.4% (249/253) of all tested isolates. Early microbial identification without susceptibility testing led to an adjustment of antibiotic regimen in 12% (24/200) of patients. CONCLUSIONS: The requisite 24 hr incubation time for microbial pathogens to reach sufficient growth for susceptibility testing and identification would be shortened by the implementation of Kiestra TLA in combination with MS, compared to the use of CM. Not only can this method optimize workflow and reduce costs, but it can allow potentially life-saving switches in antibiotic regimen to be initiated sooner.