|Author||Struck NS, Zimmermann M, Krumkamp R, Lorenz E, Jacobs T, Rieger T, Wurr S, Gunther S, Gyau Boahen K, Marks F, Sarpong N, Owusu-Dabo E, May J, Eibach D|
|Title||Cytokine profile distinguishes children with P. falciparum malaria from those with bacterial blood stream infections.|
|Journal Name||J Infect Dis|
|Month / Year||01/2020|
|Vol (No)||221 (7)|
|Page||1098 ~ 106|
BACKGROUND: Malaria presents with unspecific clinical symptoms that frequently overlap with other infectious diseases and is also a risk factor for co-infections, like non-Typhi Salmonella. Malaria RDTs are sensitive but unable to distinguish between an acute infection requiring treatment and asymptomatic malaria with a concomitant infection. We set out to test whether cytokine profiles could predict disease status and allow the differentiation between malaria and a bacterial bloodstream infection. METHODS: We created a classification model based on cytokine concentration levels of paediatric inpatients with either P. falciparum malaria or a bacterial bloodstream infection using the Luminex platform. Candidate markers were pre-selected using classification and regression trees, and the predictive strength was calculated through random forest modelling. RESULTS: Analyses revealed that a combination of 9-15 cytokines exhibited a median disease prediction accuracy of 88% (95%-percentile interval: 73%-100%). Haptoglobin, soluble Fas-Ligand, and Complement component C2 were the strongest single markers with median prediction accuracies of 82% (with 95%-percentile intervals of 71%-94%, 62%-94%, and 62%-94%, respectively). CONCLUSIONS: Cytokine profiles possess good median disease prediction accuracy and offer new possibilities for the development of innovative point-of-care tests to guide treatment decisions in malaria endemic regions.