Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
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Clin. Microbiol. Infect. · Jan 2021
Clinical course and outcomes of critically ill patients with COVID-19 infection: a systematic review.
Coronavirus disease 19 (COVID-19) is a major cause of hospital admission and represents a challenge for patient management during intensive care unit (ICU) stay. We aimed to describe the clinical course and outcomes of COVID-19 pneumonia in critically ill patients. ⋯ This systematic review, including approximately 69 000 ICU patients, demonstrates that COVID-19 infection in critically ill patients is associated with great need for life-sustaining interventions, high mortality, and prolonged length of ICU stay.
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Clin. Microbiol. Infect. · Oct 2020
ReviewTreatment of COVID-19 with convalescent plasma: lessons from past coronavirus outbreaks.
There is currently no treatment known to alter the course of coronavirus disease 2019 (COVID-19). Convalescent plasma has been used to treat a number of infections during pandemics, including severe acute respiratory syndrome coronavirus (SARS-CoV), Middle Eastern respiratory syndrome coronavirus (MERS-CoV) and now severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). ⋯ There is currently no effective treatment for COVID-19, and preliminary trials for convalescent plasma suggest that there may be some benefits. However, research to date is at high risk of bias, and randomized control trials are desperately needed to determine the efficacy and safety of this therapeutic option.
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Digitalization and artificial intelligence have an important impact on the way microbiology laboratories will work in the near future. Opportunities and challenges lie ahead to digitalize the microbiological workflows. Making efficient use of big data, machine learning, and artificial intelligence in clinical microbiology requires a profound understanding of data handling aspects. ⋯ We predict that digitalization and the usage of machine learning will have a profound impact on the daily routine of laboratory staff. Along the analytical process, the most important steps should be identified, where digital technologies can be applied and provide a benefit. The education of all staff involved should be adapted to prepare for the advances in digital microbiology.
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Clin. Microbiol. Infect. · Oct 2020
ReviewMachine learning in infection management using routine electronic health records: tools, techniques, and reporting of future technologies.
Machine learning (ML) is increasingly being used in many areas of health care. Its use in infection management is catching up as identified in a recent review in this journal. We present here a complementary review to this work. ⋯ Promising approaches for ML use in infectious diseases were identified. But building trust in these new technologies will require improved reporting. Explainability and interpretability of the models used were rarely addressed and should be further explored. Independent model validation and clinical studies evaluating the added value of ML approaches are needed.