Cytokine Profile Distinguishes Children With Plasmodium falciparum Malaria From Those With Bacterial Blood Stream Infections. (8th November 2019)

• Record Type: Journal Article
• Authors: Struck, Nicole S; Zimmermann, Marlow; Krumkamp, Ralf; Lorenz, Eva; Jacobs, Thomas; Rieger, Toni; Wurr, Stephanie; Günther, Stephan; Gyau Boahen, Kennedy; Marks, Florian; Sarpong, Nimako; Owusu-Dabo, Ellis; May, Jürgen; Eibach, Daniel
• Is Part Of: Journal of infectious diseases. Volume 221:Number 7(2020)
• Page Start: 1098
• Page End: 1106
• Publication Date: 2019-11-08
• Subjects: biomarkers -- cytokine profile -- differential diagnosis -- malaria; Communicable diseases -- Periodicals; Diseases -- Causes and theories of causation -- Periodicals; Medicine -- Periodicals; Communicable Diseases -- Periodicals; Electronic journals; 616.9
• DOI: 10.1093/infdis/jiz587
• Languages: English
• ISSNs: 0022-1899

Abstract

Abstract: Background: Malaria presents with unspecific clinical symptoms that frequently overlap with other infectious diseases and is also a risk factor for coinfections, such as non-Typhi Salmonella . Malaria rapid diagnostic tests 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 pediatric inpatients with either Plasmodium falciparum malaria or a bacterial bloodstream infection using the Luminex platform. Candidate markers were preselected using classification and regression trees, and the predictive strength was calculated through random forest modeling. Results: Analyses revealed that a combination of 7–15 cytokines exhibited a median disease prediction accuracy of 88% (95th percentile interval, 73%–100%). Haptoglobin, soluble Fas-Ligand, and complement component C2 were the strongest single markers with median prediction accuracies of 82% (with 95th 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.