REPLY
We thank Hänscheid and Grobusch for their comments. While the focus of our report is the correct selection and use of specific laboratory tests for malaria diagnosis when the disease is suspected, we acknowledge that failure to include malaria in the differential diagnosis, particularly in settings where malaria is not endemic, may lead to missed cases of this potentially fatal disease. Therefore, additional information that can be obtained from commonly ordered laboratory tests, such as a complete blood count determined with an automated hematology analyzer, may be valuable for alerting the laboratory to the possible diagnosis and prompting additional analysis or testing. While some hematology analyzers can detect hemozoin (malaria pigment) directly, others may provide evidence of malaria through evaluation of various parameters such as cell volumes, counts, and scatter by using instrument-specific algorithms (1). Studies of these algorithms in settings where malaria is not endemic using a mixture of known positive and negative specimens have demonstrated sensitivities ranging from 48.6 to 100%, with specificities of 25.3 to 100% (1, 2). While there is variability in the performance of algorithms between studies with different platforms, we feel that these methods are promising and deserve further study. In particular, we encourage prospective studies using specimens from the general population so that patients with autoimmune syndromes, hematologic disorders, and other chronic diseases are included. This would allow laboratories to evaluate whether automated hematology analyzers would provide a practical means for malaria detection in their population.
Footnotes
This is a response to a letter by Hänscheid and Grobusch (https://doi.org/10.1128/JCM.01098-17).
REFERENCES
- 1.Campuzano-Zuluaga G, Hänscheid T, Grobusch MP. 2010. Automated haematology analysis to diagnose malaria. Malar J 9:346. doi: 10.1186/1475-2875-9-346. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Mohapatra S, Samantaray JC, Arulselvi S, Panda J, Dang N, Saxena R. 2014. Comparative evaluation of two flow cytometric analyzers as diagnostic tools for the automated detection of malaria. Ann Clin Lab Sci 44:82–86. http://www.annclinlabsci.org/content/44/1/82.full.pdf. [PubMed] [Google Scholar]
