Dataset Information

Automated haematology analysis to diagnose malaria.

ABSTRACT: For more than a decade, flow cytometry-based automated haematology analysers have been studied for malaria diagnosis. Although current haematology analysers are not specifically designed to detect malaria-related abnormalities, most studies have found sensitivities that comply with WHO malaria-diagnostic guidelines, i.e. ? 95% in samples with > 100 parasites/?l. Establishing a correct and early malaria diagnosis is a prerequisite for an adequate treatment and to minimizing adverse outcomes. Expert light microscopy remains the 'gold standard' for malaria diagnosis in most clinical settings. However, it requires an explicit request from clinicians and has variable accuracy. Malaria diagnosis with flow cytometry-based haematology analysers could become an important adjuvant diagnostic tool in the routine laboratory work-up of febrile patients in or returning from malaria-endemic regions. Haematology analysers so far studied for malaria diagnosis are the Cell-Dyn®, Coulter® GEN·S and LH 750, and the Sysmex XE-2100® analysers. For Cell-Dyn analysers, abnormal depolarization events mainly in the lobularity/granularity and other scatter-plots, and various reticulocyte abnormalities have shown overall sensitivities and specificities of 49% to 97% and 61% to 100%, respectively. For the Coulter analysers, a 'malaria factor' using the monocyte and lymphocyte size standard deviations obtained by impedance detection has shown overall sensitivities and specificities of 82% to 98% and 72% to 94%, respectively. For the XE-2100, abnormal patterns in the DIFF, WBC/BASO, and RET-EXT scatter-plots, and pseudoeosinophilia and other abnormal haematological variables have been described, and multivariate diagnostic models have been designed with overall sensitivities and specificities of 86% to 97% and 81% to 98%, respectively. The accuracy for malaria diagnosis may vary according to species, parasite load, immunity and clinical context where the method is applied. Future developments in new haematology analysers such as considerably simplified, robust and inexpensive devices for malaria detection fitted with an automatically generated alert could improve the detection capacity of these instruments and potentially expand their clinical utility in malaria diagnosis.

SUBMITTER: Campuzano-Zuluaga G

PROVIDER: S-EPMC3013084 | biostudies-other | 2010

REPOSITORIES: biostudies-other

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Automated haematology analysis to diagnose malaria.

Campuzano-Zuluaga Germán G Hänscheid Thomas T Grobusch Martin P MP

Malaria journal 20101130

For more than a decade, flow cytometry-based automated haematology analysers have been studied for malaria diagnosis. Although current haematology analysers are not specifically designed to detect malaria-related abnormalities, most studies have found sensitivities that comply with WHO malaria-diagnostic guidelines, i.e. ≥ 95% in samples with > 100 parasites/μl. Establishing a correct and early malaria diagnosis is a prerequisite for an adequate treatment and to minimizing adverse outcomes. Expe ...[more]

PMID: 21118557

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Project description:BackgroundThe automated haematology analyzer XN-31 prototype (XN-31p) is a new flow cytometry-based device developed to measure the number and the ratio of malaria-infected red blood cells (MI-RBC) with a complete blood count (CBC). The XN-31p can provide results in about one minute and also can simultaneously provide information on the malaria parasite (Plasmodium) species. In this study, clinical testing of the XN-31p was performed using blood samples from patients with imported malaria in Japan.MethodsBlood samples were collected from 80 patients who visited the hospital of the National Center for Global Health and Medicine, Tokyo, Japan, for malaria diagnosis from January 2017 to January 2019. The test results by the XN-31p were compared with those by other standard methods, such as microscopic observation, rapid diagnostic tests and the nested PCR.ResultsThirty-three patients were diagnosed by the nested PCR as being malaria positive (28 Plasmodium falciparum, 2 Plasmodium vivax, 1 Plasmodium knowlesi, 1 mixed infection of P. falciparum and Plasmodium malariae, and 1 mixed infection of P. falciparum and Plasmodium ovale), and the other 47 were negative. The XN-31p detected 32 patients as "MI-RBC positive", which almost matched the results by the nested PCR and, in fact, completely matched with the microscopic observations. The ratio of RBCs infected with malaria parasites as determined by the XN-31p showed a high correlation coefficient of more than 0.99 with the parasitaemia counted under microscopic observation. The XN-31p can analyse the size and nucleic acid contents of each cell, and the results were visualized on a two-dimensional cytogram termed the "M scattergram". Information on species and developmental stages of the parasites could also be predicted from the patterns visualized in the M scattergrams. The XN-31p showed a positive coincidence rate of 0.848 with the nested PCR in discriminating P. falciparum from the other species.ConclusionsThe XN-31p could rapidly provide instructive information on the ratio of MI-RBC and the infecting Plasmodium species. It was regarded to be of great help for the clinical diagnosis of malaria.

Project description:BackgroundSimple and accurate diagnosis is a key component of malaria control programmes. Microscopy is the current gold standard, however it requires extensive training and the results largely rely on the skill of the microscopists. Malaria rapid diagnostic tests (RDT) can be performed with minimal training and offer timely diagnosis, but results are not quantitative. Moreover, some Plasmodium falciparum parasites have evolved and can no longer be detected by existing RDT. Developed by the Sysmex Corporation, the XN-31 prototype (XN-31p) is an automated haematology analyser capable of detecting Plasmodium-infected erythrocytes and providing species differentiation and stage specific parasite counts in venous blood samples without any preparation in approximately one minute. However, factors such as stable electricity supply in a temperature-controlled room, cost of the instrument and its initial set-up, and need for proprietary reagents limit the utility of the XN-31p across rural settings. To overcome some of these limitations, a hub and spoke diagnosis model was designed, in which peripheral health facilities were linked to a central hospital where detection of Plasmodium infections by the XN-31p would take place. To explore the feasibility of this concept, the applicability of capillary blood samples with the XN-31p was evaluated with respect to the effect of sample storage time and temperature on the stability of results.MethodsPaired capillary and venous blood samples were collected from 169 malaria-suspected outpatients in Homa Bay County Referral Hospital, Kenya. Malaria infections were diagnosed with the XN-31p, microscopy, RDT, and PCR. Capillary blood samples were remeasured on the XN-31p after 24 h of storage at either room (15-25 °C) or chilled temperatures (2-8 °C).ResultsIdentical results in malaria diagnosis were observed between venous and capillary blood samples processed immediately after collection with the XN-31p. Relative to PCR, the sensitivity and specificity of the XN-31p with capillary blood samples were 0.857 and 1.000, respectively. Short-term storage of capillary blood samples at chilled temperatures had no adverse impact on parasitaemia and complete blood counts (CBC) measured by the XN-31p.ConclusionThese results demonstrate the potential of the XN-31p to improve routine malaria diagnosis across remote settings using a hub and spoke model.

Project description:BackgroundThe erythrocytic stage of Plasmodium falciparum parasites in humans is clinically important, as the parasites at this growth stage causes malarial symptoms. Most of the currently available anti-malarial drugs target this stage, but the emergence and spread of parasites resistant to anti-malarial drugs are a major challenge to global eradication efforts; therefore, the development of novel medicines is urgently required. In this study, the in vitro anti-malarial activity of five current anti-malarial drugs (artemisinin, atovaquone, chloroquine, mefloquine, and pyrimethamine) and 400 compounds from the Pathogen Box provided by the Medicines for Malaria Venture on P. falciparum parasites was characterized using the XN-30 analyzer. Furthermore, the outcomes obtained using the analyser were classified according to the parasitaemias of total and each developmental stages.ResultsThe growth inhibition rate and the half-maximal (50%) inhibitory concentration (IC50) of the five current anti-malarial drugs were calculated from the parasitaemia detected using the XN-30 analyzer. Respective strains and drugs presented strongly fitted sigmoidal curves, and the median SD at all tested concentrations was 1.6, suggesting that the variation in values measured with the analyser was acceptably low for the comparison of drug efficacy. Furthermore, the anti-malarial activity of the 400 compounds from the Pathogen Box was tested, and 141 drugs were found to be effective. In addition, the efficacy was classified into 4 types (Type I, parasites were arrested or killed without DNA replication; Type II, parasites were arrested or killed similar to Type I, and the parasitaemia was apparently decreased; Type III, parasites progressed to trophozoite without sufficient DNA replication; and Type IV, parasites were arrested at late trophozoite or schizont after DNA replication).ConclusionThe current study demonstrates that the XN-30 analyzer objectively, reproducibly, and easily evaluated and characterized the anti-malarial efficacy of various compounds. The results indicate the potential of the XN-30 analyzer as a powerful tool for drug discovery and development in addition to its use as an important diagnostic tool.

Project description:BackgroundThere are a variety of approaches being used for malaria surveillance. While active and reactive case detection have been successful in localized areas of low transmission, concerns over scalability and sustainability keep the approaches from being widely accepted. Mobile health interventions are poised to address these shortcomings by automating and standardizing portions of the surveillance process. In this study, common challenges associated with current data aggregation methods have been quantified, and a web-based mobile phone application is presented to reduce the burden of reporting rapid diagnostic test (RDT) results in low-resource settings.MethodsDe-identified completed RDTs were collected at 14 rural health clinics as part of a malaria epidemiology study at Macha Research Trust, Macha, Zambia. Tests were imaged using the mHAT web application. Signal intensity was measured and a binary result was provided. App performance was validated by: (1) comparative limits of detection, investigated against currently used laboratory lateral flow assay readers; and, (2) receiver operating characteristic analysis comparing the application against visual inspection of RDTs by an expert. Secondary investigations included analysis of time-to-aggregation and data consistency within the existing surveillance structures established by Macha Research Trust.ResultsWhen compared to visual analysis, the mHAT app performed with 91.9% sensitivity (CI 78.7, 97.2) and specificity was 91.4% (CI 77.6, 97.0) regardless of device operating system. Additionally, an analysis of surveillance data from January 2017 through mid-February 2019 showed that while the majority of the data packets from satellite clinics contained correct data, 36% of data points required correction by verification teams. Between November 2018 and mid-February 2019, it was also found that 44.8% of data was received after the expected submission date, although most (65.1%) reports were received within 2 days.ConclusionsOverall, the mHAT mobile app was observed to be sensitive and specific when compared to both currently available benchtop lateral flow readers and visual inspection. The additional benefit of automating and standardizing LFA data collection and aggregation poses a vital improvement for low-resource health facilities and could increase the accuracy and speed of data reporting in surveillance campaigns.

Project description:BACKGROUND:Widespread elimination of malaria requires an ultra-sensitive detection method that can detect low parasitaemia levels seen in asymptomatic carriers who act as reservoirs for further transmission of the disease, but is inexpensive and easy to deploy in the field in low income settings. It was hypothesized that a new method of malaria detection based on infrared spectroscopy, shown in the laboratory to have similar sensitivity to PCR based detection, could prove effective in detecting malaria in a field setting using cheap portable units with data management systems allowing them to be used by users inexpert in spectroscopy. This study was designed to determine whether the methodology developed in the laboratory could be translated to the field to diagnose the presence of Plasmodium in the blood of patients presenting at hospital with symptoms of malaria, as a precursor to trials testing the sensitivity of to detect asymptomatic carriers. METHODS:The field study tested 318 patients presenting with suspected malaria at four regional clinics in Thailand. Two portable infrared spectrometers were employed, operated from a laptop computer or a mobile telephone with in-built software that guided the user through the simple measurement steps. Diagnostic modelling and validation testing using linear and machine learning approaches was performed against the gold standard qPCR. Sample spectra from 318 patients were used for building calibration models (112 positive and 110 negative samples according to PCR testing) and independent validation testing (39 positive and 57 negatives samples by PCR). RESULTS:The machine learning classification (support vector machines; SVM) performed with 92% sensitivity (3 false negatives) and 97% specificity (2 false positives). The Area Under the Receiver Operation Curve (AUROC) for the SVM classification was 0.98. These results may be better than as stated as one of the spectroscopy false positives was infected by a Plasmodium species other than Plasmodium falciparum or Plasmodium vivax, not detected by the PCR primers employed. CONCLUSIONS:In conclusion, it was demonstrated that ATR-FTIR spectroscopy could be used as an efficient and reliable malaria diagnostic tool and has the potential to be developed for use at point of care under tropical field conditions with spectra able to be analysed via a Cloud-based system, and the diagnostic results returned to the user's mobile telephone or computer. The combination of accessibility to mass screening, high sensitivity and selectivity, low logistics requirements and portability, makes this new approach a potentially outstanding tool in the context of malaria elimination programmes. The next step in the experimental programme now underway is to reduce the sample requirements to fingerprick volumes.

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Automated haematology analysis to diagnose malaria.

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Automated haematology analysis to diagnose malaria.

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