Analysis reveals dominant risk factors, clinical symptoms and treatment outcomes in COVID-19 patients
In collaboration with colleagues from Swiss hospitals and Canadian Universities, researchers from the D-BSSE Machine Learning and Computational Biology group conducted a large systematic review and meta-analysis of COVID-19 research publications. The study led by Catherine Jutzeler confirms earlier findings that older age and being male as well as different pre-existing comorbidities count as risk factors. Children and neonates appear to be the least vulnerable cohort.
Find original publication (open access):
Jutzeler, C R, L Bourguignong, C V Weis, B Tong, C Wong, B Rieck, H Pargger, S Tschudin-Sutter, A Egli, K Borgwardt and M Walter (2020) external pageComorbidities, clinical signs and symptoms, laboratory findings, imaging features, treatment strategies, and outcomes in adult and pediatric patients with COVID-19: A systematic review and meta-analysiscall_made. Travel Medicine and Infectious Disease, https://doi.org/10.1016/j.tmaid.2020.101825
Find information on the D-BSSE Machine Learning and Computational Biology lab.