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      Diagnostic accuracy of fluorescence flow-cytometry technology using Sysmex XN-31 for imported malaria in a non-endemic setting Translated title: Précision diagnostique de la technique de cytométrie de flux en fluorescence utilisant le Sysmex XN-31 pour le paludisme d’importation en zone non endémique

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          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 as falciparumor 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.

          Translated abstract

          Le diagnostic du paludisme basé sur la microscopie est rendu difficile par la disparition progressive des microscopistes expérimentés en zone non-endémique. À côté des méthodes conventionnelles, la technique de cytométrie de flux en fluorescence utilisant le Sysmex XN-31, un automate d’analyse hématologique, a été enregistrée pour participer au diagnostic du paludisme. L’objectif de cette étude prospective, monocentrique et non-interventionelle était d’évaluer la précision diagnostique du XN-31 pour le diagnostic initial et le suivi des cas de paludisme d’importation en comparaison des tests de référence dont la microscopie, l’amplification isothermale en boucle, et des tests de diagnostic rapide. Durant une période d’un an, 357 échantillons de sang ont été analysés, dont 248 négatifs et 109 positifs pour le paludisme. En comparaison de la microscopie, le XN-31 a montré une sensibilité de 100 % (95 % CI : 97.13-100) et une spécificité de 98.39 % (95 % CI : 95.56-100) pour le diagnostic initial des cas de paludisme d’importation. De plus, l’identification des espèces falciparumet non- falciparumainsi que la parasitémie ont été précises dans un temps très court en comparaison des autres méthodes. Nous avons aussi démontré que le XN-31 était une méthode fiable pour le suivi des patients à J3, J7 et J28. Le diagnostic du paludisme peut être amélioré en zone non-endémique par l’utilisation d’automates d’hématologie spécialisés, associés à la microscopie standard ou d’autres méthodes en développement telle que l’intelligence artificielle appliquée à la lecture des lames de sang. Dans la mesure où le XN-31 produit un diagnostic précis en une minute, cela peut réduire le délai avant le traitement et donc améliorer l’issue pour les patients souffrant de paludisme.

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          Most cited references41

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          Malaria: Biology and Disease.

          Malaria has been a major global health problem of humans through history and is a leading cause of death and disease across many tropical and subtropical countries. Over the last fifteen years renewed efforts at control have reduced the prevalence of malaria by over half, raising the prospect that elimination and perhaps eradication may be a long-term possibility. Achievement of this goal requires the development of new tools including novel antimalarial drugs and more efficacious vaccines as well as an increased understanding of the disease and biology of the parasite. This has catalyzed a major effort resulting in development and regulatory approval of the first vaccine against malaria (RTS,S/AS01) as well as identification of novel drug targets and antimalarial compounds, some of which are in human clinical trials.
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            Statistical methodology: I. Incorporating the prevalence of disease into the sample size calculation for sensitivity and specificity.

            Careful consideration of statistical issues related to the choice of a sample size is critical for achieving meaningful results in research studies designed to evaluate diagnostic tests. When assessing the ability of a diagnostic test to screen for disease, the parameters sensitivity, specificity, and predictive values are of interest. Study sample size requirements can be calculated based on a clinically acceptable degree of precision, the hypothesized values of sensitivity and specificity, and the estimated prevalence of disease in the target population. The simple methods and tables in this paper guide the researcher when deciding how many subjects to sample in a study designed to estimate both the sensitivity and the specificity of a diagnostic test, given a specified precision and estimated disease prevalence.
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              Internet of medical things (IoMT)-integrated biosensors for point-of-care testing of infectious diseases

              On global scale, the current situation of pandemic is symptomatic of increased incidences of contagious diseases caused by pathogens. The faster spread of these diseases, in a moderately short timeframe, is threatening the overall population wellbeing and conceivably the economy. The inadequacy of conventional diagnostic tools in terms of time consuming and complex laboratory-based diagnosis process is a major challenge to medical care. In present era, the development of point-of-care testing (POCT) is in demand for fast detection of infectious diseases along with “on-site” results that are helpful in timely and early action for better treatment. In addition, POCT devices also play a crucial role in preventing the transmission of infectious diseases by offering real-time testing and lab quality microbial diagnosis within minutes. Timely diagnosis and further treatment optimization facilitate the containment of outbreaks of infectious diseases. Presently, efforts are being made to support such POCT by the technological development in the field of internet of medical things (IoMT). The IoMT offers wireless-based operation and connectivity of POCT devices with health expert and medical centre. In this review, the recently developed POC diagnostics integrated or future possibilities of integration with IoMT are discussed with focus on emerging and re-emerging infectious diseases like malaria, dengue fever, influenza A (H1N1), human papilloma virus (HPV), Ebola virus disease (EVD), Zika virus (ZIKV), and coronavirus (COVID-19). The IoMT-assisted POCT systems are capable enough to fill the gap between bioinformatics generation, big rapid analytics, and clinical validation. An optimized IoMT-assisted POCT will be useful in understanding the diseases progression, treatment decision, and evaluation of efficacy of prescribed therapy.
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                Author and article information

                Journal
                Parasite
                Parasite
                parasite
                Parasite
                EDP Sciences
                1252-607X
                1776-1042
                2022
                31 May 2022
                : 29
                : ( publisher-idID: parasite/2022/01 )
                : 31
                Affiliations
                [1 ] Service de Parasitologie et Mycologie Médicale, Groupement Hospitalier Nord, Hospices Civils de Lyon69004 LyonFrance
                [2 ] Université de Lyon, Université Lyon 1, CNRS, INSA, CPE-Lyon, ICBMS, UMR 524669100 VilleurbanneFrance
                [3 ] Service des Maladies Infectieuses et Tropicales, Hôpital de la Croix-Rousse, Hospices Civils de Lyon69004 LyonFrance
                [4 ] CIRI Équipe PH3ID – INSERM – U1111– UCBL Lyon 1 – CNRS – UMR5308 – ENS de Lyon69007 LyonFrance
                [5 ] Service d’accueil des urgences, Hôpital de la Croix-Rousse, Hospices Civils de Lyon69004 LyonFrance
                [6 ] Service de Réanimation et Urgences Pédiatriques, Hôpital Femme-Mere-Enfant, Hospices Civils de Lyon69500 LyonFrance
                [7 ] Service d’accueil des urgences, Hôpital Edouard Herriot, Hospices Civils de Lyon69008 LyonFrance
                [8 ] Service d’accueil des urgences, Hôpital Lyon Sud, Hospices Civils de Lyon69310 LyonFrance
                [9 ] Université de Lyon, Université Claude Bernard Lyon 1, HESPER EA 742569008 LyonFrance
                [10 ] Hospices Civils de Lyon, Hôpital Edouard Herriot, Service de Médecine Intensive-Réanimation69008 LyonFrance
                [11 ] Service Pharmacie, Groupement Hospitalier Nord, Hospices Civils de Lyon69004 LyonFrance
                Author notes
                [* ]Corresponding author: Stephane.picot@ 123456chu-lyon.fr
                Author information
                http://orcid.org/0000-0002-5735-6759
                Article
                parasite210161 10.1051/parasite/2022031
                10.1051/parasite/2022031
                9153516
                35638753
                0b439e25-f1ae-4cef-9e02-3b2637a3473f
                © S. Picot et al., published by EDP Sciences, 2022

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 01 December 2021
                : 16 May 2022
                Page count
                Figures: 2, Tables: 2, Equations: 0, References: 40, Pages: 9
                Funding
                Funded by: Sysmex (Japan)
                Categories
                Research Article

                malaria,plasmodium,diagnostic accuracy,sysmex xn-31,rdt,lamp,microscopy,pcr

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