Researchers have developed a method for assessing the number and structure of aggregated blood platelets (or thrombocytes) that can potentially help quantify the risk of a severe COVID-19 infection. As a result, they have identified a predictive biomarker for the seriousness of a COVID-19 infection. This will allow physicians to adjust treatment at an early stage. The researchers used a method from image-based flow cytometry that permits the rapid analysis of interactions between large numbers of blood cells.
When infected with the Sars-CoV-2 virus, the human body produces a series of immune responses. One of them involves platelets, also known as thrombocytes, sticking to immune cells to form clumps, or aggregates, of cells in the bloodstream. In a study using image-based flow cytometry, a team of researchers working with Oliver Hayden, a professor of biomedical electronics, demonstrated a rapid rise in concentrations of platelet aggregates in patients admitted to intensive care with COVID-19 infections.
This enabled them to identify a biomarker for predicting the risk of severe illness in COVID-19 patients. The result was made possible by the optimal interdisciplinary conditions offered by the central TranslaTUM institute to TUM engineers for collaboration with medical researchers at Klinikum München rechts der Isar.