ArticleParasite (Paris, France)2022
Diagnostic accuracy of fluorescence flow-cytometry technology using Sysmex XN-31 for imported malaria in a non-endemic setting.
Article in Parasite (Paris, France), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Diagnostic role of Sysmex hematology analyzer in the detection of malaria: A systematic review and meta-analysis.PloS one · 2024Pooled it
- A comparison of the cost-effectiveness of the current standard of care and of the haematology analyser XN31-microscopy combination for diagnosing malaria in a nonendemic country.Memorias do Instituto Oswaldo Cruz · 2026Article
- Performance evaluation of the automated haematology analyzer XN-31 for malaria diagnosis in Plasmodium vivax-dominant regions of Thailand.Malaria journal · 2025Article
- Article
- Clinical performance testing of the automated haematology analyzer XN-31 prototype using whole blood samples from patients with imported malaria in Japan.Malaria journal · 2022Article
- Digital microscopy and artificial intelligence could profoundly contribute to malaria diagnosis in elimination settings.Frontiers in artificial intelligence · 2022Article
Corrections and comments
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Authors and funding
14 authors at 3 institutions in 1 country.
Funding
Abstract
Malaria diagnosis based on microscopy is impaired by the gradual disappearance of experienced microscopists in non-endemic areas. Aside from the conventional diagnostic methods, fluorescence flow cytometry technology using Sysmex XN-31, an automated haematology analyser, has been registered to support malaria diagnosis. The aim of this prospective, monocentric, non-interventional study was to evaluate the diagnostic accuracy of the XN-31 for the initial diagnosis or follow-up of imported malaria cases compared to the reference malaria tests including microscopy, loop mediated isothermal amplification, and rapid diagnostic tests. Over a one-year period, 357 blood samples were analysed, including 248 negative and 109 positive malaria samples. Compared to microscopy, XN-31 showed sensitivity of 100% (95% CI: 97.13-100) and specificity of 98.39% (95% CI: 95.56-100) for the initial diagnosis of imported malaria cases. Moreover, it provided accurate species identification asfalciparumor non-falciparumand parasitaemia determination in a very short time compared to other methods. We also demonstrated that XN-31 was a reliable method for patient follow-up on days 3, 7, and 28. Malaria diagnosis can be improved in non-endemic areas by the use of dedicated haematology analysers coupled with standard microscopy or other methods in development, such as artificial intelligence for blood slide reading. Given that XN-31 provided an accurate diagnosis in 1 min, it may reduce the time interval before treatment and thus improve the outcome of patient who have malaria.
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Registered trials
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