Browsing by Author "Jennifer Luchavez"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • No Thumbnail Available
    PublicationMetadata only
    Evaluation of three parasite lactate dehydrogenase-based rapid diagnostic tests for the diagnosis of falciparum and vivax malaria
    (2009-12-01) Elizabeth A. Ashley; Malek Touabi; Margareta Ahrer; Robert Hutagalung; Khayae Htun; Jennifer Luchavez; Christine Dureza; Stephane Proux; Mara Leimanis; Myo Min Lwin; Alena Koscalova; Eric Comte; Prudence Hamade; Anne Laure Page; François Nosten; Philippe J. Guerin; Epicentre; Imperial College Healthcare NHS Trust; Médecins Sans Frontières-Switzerland; Gokila; Shoklo Malaria Research Unit; Mahidol University; Nuffield Department of Clinical Medicine; Medecins Sans Frontieres; Médecins Sans Frontières Malaria Working Group; Malaria Consortium
    Background. In areas where non-falciparum malaria is common rapid diagnostic tests (RDTs) capable of distinguishing malaria species reliably are needed. Such tests are often based on the detection of parasite lactate dehydrogenase (pLDH). Methods. In Dawei, southern Myanmar, three pLDH based RDTs (CareStart Malaria pLDH (Pan), CareStart Malaria pLDH (Pan, Pf) and OptiMAL-IT®)were evaluated in patients presenting with clinically suspected malaria. Each RDT was read independently by two readers. A subset of patients with microscopically confirmed malaria had their RDTs repeated on days 2, 7 and then weekly until negative. At the end of the study, samples of study batches were sent for heat stability testing. Results. Between August and November 2007, 1004 patients aged between 1 and 93 years were enrolled in the study. Slide microscopy (the reference standard) diagnosed 213 Plasmodium vivax (Pv) monoinfections, 98 Plasmodium falciparum (Pf) mono-infections and no malaria in 650 cases. The sensitivities (sens) and specificities (spec), of the RDTs for the detection of malaria were- CareStart MalariaTMpLDH (Pan) test: sens 89.1% [CI9584.2-92.6], spec 97.6% [CI9596.5-98.4]. OptiMal-IT®: Pf+/- other species detection: sens 95.2% [CI9587.5-98.2], spec 94.7% [CI9593.3-95.8]; non-Pf detection alone: sens 89.6% [CI9583.6-93.6], spec 96.5% [CI9594.8-97.7]. CareStart Malaria pLDH (Pan, Pf): Pf+/- other species: sens 93.5% [CI9585.4-97.3], spec 97.4% [95.9-98.3]; non-Pf: sens 78.5% [CI9571.1-84.4], spec 97.8% [CI9596.3-98.7]. Inter-observer agreement was excellent for all tests (kappa > 0.9). The median time for the RDTs to become negative was two days for the CareStart Malaria tests and seven days for OptiMAL-IT®. Tests were heat stable up to 90 days except for OptiMAL-IT®(Pf specific pLDH stable to day 20 at 35°C). Conclusion. None of the pLDH-based RDTs evaluated was able to detect non-falciparum malaria with high sensitivity, particularly at low parasitaemias. OptiMAL-IT®performed best overall and would perform best in an area of high malaria prevalence among screened fever cases. However, heat stability was unacceptable and the number of steps to perform this test is a significant drawback in the field. A reliable, heat-stable, highly sensitive RDT, capable of diagnosing all Plasmodium species has yet to be identified. © 2009 Ashley et al; licensee BioMed Central Ltd.
  • No Thumbnail Available
    PublicationMetadata only
    Performance of a fully‐automated system on a WHO malaria microscopy evaluation slide set
    (2021-12-01) Matthew P. Horning; Charles B. Delahunt; Christine M. Bachman; Jennifer Luchavez; Christian Luna; Liming Hu; Mayoore S. Jaiswal; Clay M. Thompson; Sourabh Kulhare; Samantha Janko; Benjamin K. Wilson; Travis Ostbye; Martha Mehanian; Roman Gebrehiwot; Grace Yun; David Bell; Stephane Proux; Jane Y. Carter; Wellington Oyibo; Dionicia Gamboa; Mehul Dhorda; Ranitha Vongpromek; Peter L. Chiodini; Bernhards Ogutu; Earl G. Long; Kyaw Tun; Thomas R. Burkot; Ken Lilley; Courosh Mehanian; Mahidol Oxford Tropical Medicine Research Unit; Gokila; Universidad Peruana Cayetano Heredia; Kenya Medical Research Institute; Amref Health Africa; London School of Hygiene & Tropical Medicine; Centers for Disease Control and Prevention; James Cook University; University of Washington; Mahidol University; University of Lagos; Arizona State University; Australian Defence Force Malaria and Infectious Disease Institute; Independent Consultant; Asia Regional Centre; Defence Services Medical Academy; Creative Creek, LLC; Intellectual Ventures Global Good Fund; Intellectual Ventures
    Background: Manual microscopy remains a widely-used tool for malaria diagnosis and clinical studies, but it has inconsistent quality in the field due to variability in training and field practices. Automated diagnostic systems based on machine learning hold promise to improve quality and reproducibility of field microscopy. The World Health Organization (WHO) has designed a 55-slide set (WHO 55) for their External Competence Assessment of Malaria Microscopists (ECAMM) programme, which can also serve as a valuable benchmark for automated systems. The performance of a fully-automated malaria diagnostic system, EasyScan GO, on a WHO 55 slide set was evaluated. Methods: The WHO 55 slide set is designed to evaluate microscopist competence in three areas of malaria diagnosis using Giemsa-stained blood films, focused on crucial field needs: malaria parasite detection, malaria parasite species identification (ID), and malaria parasite quantitation. The EasyScan GO is a fully-automated system that combines scanning of Giemsa-stained blood films with assessment algorithms to deliver malaria diagnoses. This system was tested on a WHO 55 slide set. Results: The EasyScan GO achieved 94.3 % detection accuracy, 82.9 % species ID accuracy, and 50 % quantitation accuracy, corresponding to WHO microscopy competence Levels 1, 2, and 1, respectively. This is, to our knowledge, the best performance of a fully-automated system on a WHO 55 set. Conclusions: EasyScan GO’s expert ratings in detection and quantitation on the WHO 55 slide set point towards its potential value in drug efficacy use-cases, as well as in some case management situations with less stringent species ID needs. Improved runtime may enable use in general case management settings.