Classification of infectious diseases based on chemiluminescent signatures of phagocytes in whole blood

摘要

ObjectivesDespite medical advances, infectious diseases are still a major cause of mortality and morbidity, disability and socio-economic upheaval worldwide. Early diagnosis, appropriate choice and immediate initiation of antibiotic therapy can greatly affect the outcome of any kind of infection. Phagocytes play a central role in the innate immune response of the organism to infection. They comprise the first-line of defense against infectious intruders in our body, being able to produce large quantities of reactive oxygen species, which can be detected by means of chemiluminescence (CL). The data preparation approach implemented in this work corresponds to a dynamic assessment of phagocytic respiratory burst localization in a luminol-enhanced whole blood CL system. We have previously applied this approach to the problem of identifying various intra-abdominal pathological processes afflicting peritoneal dialysis patients in the Nephrology department and demonstrated 84.6% predictive accuracy with the C4.5 decision-tree algorithm. In this study, we apply the CL-based approach to a larger sample of patients from two departments (Nephrology and Internal Medicine) with the aim of finding the most effective and interpretable feature sets and classification models for a fast and accurate identification of several infectious diseases.