2 research outputs found
Influence of dengue endemicity on malaria identification by automated hematology analyzer – Beckman Coulter LH750: A hospital-based cross-sectional study
Aim: Automated hematology analyzers have been used to develop indices and algorithms for diagnosing malaria. We believe that the practical utility of such indices depends on the infection profile in the community since the type of infection determines the hematological parameters and consequently their power to discriminate malaria. Our region is endemic for malaria and dengue. Our aim was to verify the utility of the published malaria factor (MF) in our setting. Materials and Methods: Anticoagulated blood from clinically suspected cases of malaria and dengue were analyzed. The standard deviation and mean (M) values of all the leukocytes were obtained and the MF was calculated. Results: The MF showed a sensitivity and specificity of 75% and 55.1% in identifying malaria at a cutoff of 4.2 when the control group (CG) included dengue-positive (DP) patients and a sensitivity and specificity of 93.4% and 65.2% when the CG did not include DP cases. Using another set of parameters, we developed a Malaria Discriminant Index which showed a sensitivity and specificity of 94.4% and 73.9% in identifying malaria in the absence of dengue at a cutoff of 1.19 and a sensitivity and specificity of 85.5% and 61.7% at a cut off of 1.26 when dengue patients were included in the CG. Conclusion: This study emphasizes the need to verify the utility of indices/factors developed in regions not having similar endemic profiles before utilizing them in the clinical setting as other infections can influence the discriminant capacity