The Diagnostic Performance of a Sysmex XN-31 Automated Malaria Analyzer vs. Expert Microscopy.

Abstract

Introduction: Malaria is a common and life-threatening infection. Malaria diagnosis needs to be fast and reliable. Although malaria microscopy is currently the gold standard, it is laborious, requires extensive training, and relies heavily on the proficiency of microscopists. Though malaria rapid tests are widely used, they show poor sensitivity at low parasitemia levels, are affected by gene deletions, and offer only qualitative results. There is a need to explore new techniques for the diagnosis of malaria.

Methodology: A single-center, cross-sectional study evaluated the diagnostic performance of the Sysmex XN-31 automated analyzer for detecting malaria parasites compared to expert microscopy. The primary objective was to assess the XN-31's sensitivity, specificity, and ability to quantify malaria parasites relative to microscopy, the current gold standard. Blood samples from 310 adult patients undergoing routine malaria testing in a hospital setting were used. This included 118 confirmed malaria-positive cases. The Sysmex XN-31 results were compared to blinded expert microscopy on the same samples. Dried blood spot samples were collected for any discrepancies and resolved using molecular testing.

Results: This study analyzed 310 patient samples for malaria using both microscopy and the XN-31 analyzer. Microscopy identified 122 positive samples (39%), with P. falciparum being the most prevalent species. Expert malaria microscopy demonstrated a sensitivity of 97.6% and a specificity of 100%. The XN-31 analyzer showed a sensitivity of 100% and a specificity of 99.46%. In malaria speciation, the XN-31 correctly flagged P. falciparum in 116 out of 117 cases (99.1%) among 125 positive cases. Additionally, five nonfalciparum malaria cases (Plasmodium malariae-four cases and Plasmodium ovale-one case) were accurately flagged as 'Malaria (Others).' However, five P. falciparum cases were incorrectly flagged as 'Malaria (Others),' highlighting limitations in malaria speciation by the analyzer. Statistical analysis revealed a strong correlation (Spearman coefficient of 0.8) between the parasite density measured via microscopy and the XN-31. Passing-Bablok regression indicated a strong linear relationship between these two methods.

Conclusion: The Sysmex XN-31 analyzer provides a quick and accurate method for the diagnosis of malaria. It detects, quantifies, and speciates plasmodium infections in less than 1 minute. Our study showed that the analyzer shows high sensitivity and specificity comparable to those of expert microscopy in detecting Plasmodium species, making it a promising alternative to current diagnostic methods. By overcoming the numerous limitations of existing tests, the XN-31 proves to be well-suited for malaria testing, especially in malaria-endemic regions.