A blood test has the potential to identify the cause of a fever by analyzing changes in gene activity, whether it is caused by bacteria, viruses, or an inflammatory disease. In cases where children are hospitalized for fever, about three-quarters of them do not receive a diagnosis. Current diagnostic tools that look for pathogens can be slow and unreliable. However, genetic tests offer a promising alternative as certain genes respond to diseases by turning on or off.
Researchers at Imperial College London, led by Myrsini Kaforou, conducted a study where they analyzed the gene expression in blood samples from 1212 children diagnosed with 18 different infectious or inflammatory diseases that cause fever. They used a machine learning model to analyze the data and identified 161 genes that correlate with diseases across six categories: bacterial infections, viral infections, inflammatory diseases, malaria, tuberculosis, or Kawasaki disease. The model was then validated using a separate group of 411 children with fever and showed excellent accuracy with a score of 0.89 to 1 on a scale of 0 to 1.
The use of this blood test could expedite the diagnostic process, ensure appropriate treatment, and help reduce unnecessary antibiotic use, which contributes to antibiotic resistance. However, further validation in larger data sets is needed before it can be used in clinical settings. The researchers are also working on expanding the list of diseases covered by the test by recruiting more patients and generating more data.
Overall, this blood test is considered a significant step forward in precision medicine for infectious and inflammatory diseases in children, but more research is required to fully establish its effectiveness and applicability.
