Abnormal scattergrams and cell population data generated by fully automated hematological analyzers: New tools for screening malaria infection?. (21st February 2018) - Buoro, S.; Manenti, B.; Seghezzi, M.; Moioli, V.; Bagorria, M.; Callegaro, A.; Ottomano, C.; Lippi, G.
Abstract: Introduction: Malaria is a life‐threatening infectious disease, which has been for long confined to specific endemic areas. Nevertheless, the recent increase in immigration flows from endemic regions and imported cases has reemphasized many diagnostic challenges in Western countries, thus paving the way to introduce rapid and accurate strategies for screening subjects with suspected Malaria infection. Therefore, the aim of this article was to describe our recent experience with Sysmex XN‐module for rapid screening of subjects with suspected Malaria. Methods: Fourteen patients admitted to the Emergency Department (Papa Giovanni XXIII Hospital Bergamo, Italy) with a clinical suspicion of Malaria infection were evaluated, along with 1047 control samples. The analysis of peripheral blood was performed with XN‐module, and results were then compared to optical microscopy. Results: Nine patients were positive to Plasmodim falciparum, 3 to Plasmodim vivax, one to Plasmodim ovale, and one to Plasmodim malarie . Characteristic abnormalities could be observed in both white blood cell differential (WDF) and white cell nucleated (WNR) scattergrams (sensitivity 0.64 and specificity 1.0) in 9 samples with parasites at gametocyte or schizos stage irrespective of Plasmodium species and parasitic index, while characteristic scattergram abnormalities could not be seen in the 5 samples containing only parasites at the trophozoites stage. In these cases, specific variations of some cell population data (CPD) could be recorded (sensitivity 1.00 and specificity 0.91). Conclusion: The peculiar abnormalities observed in CPDs, WDF, and WNR‐scattergrams may raise a definite suspicion of Malaria infection. Further studies should then be planned for validating these preliminary findings and assessing whether these specific abnormalities may be incorporated in rapid and inexpensive Malaria diagnostic algorithms.