"Blood tests could potentially enhance the accuracy of malaria diagnoses in research circumstances"
In a groundbreaking study published in the prestigious journal eLife, researchers from the Mahidol Oxford Tropical Medicine Research Unit (MORU) have developed a statistical model that could help distinguish severe malaria from other severe illnesses in African children.
Diagnosing severe malaria in children in Africa is challenging due to the presence of malaria parasites in both healthy and severely ill children. This can lead to misdiagnosis, potentially delaying life-saving antibiotic care and skewing the results of studies of new treatments for malaria.
The study, conducted by researchers from MORU, was published in the subject area of Epidemiology and Global Health in eLife. The researchers found that by focusing on platelet and white blood cell counts, they could identify children who were misdiagnosed as having severe malaria.
According to the researchers, severe malaria kills about 400,000 children in Africa each year. By improving the accuracy of diagnosis, the new model could save countless lives.
John Bleho, the Media and Communications contact at MORU, can be reached at [email protected] or at 90 537 567 8460.
The study, published under the DOI: 10.7554/eLife.69698, also revealed that people with glucose-6-phosphate dehydrogenase deficiency probably have some protection from malaria. This benefit was likely obscured in previous studies by the high rate of misdiagnoses.
eLife is a non-profit organization that operates a platform for research communication, with a mission to accelerate discovery by recognizing responsible behaviors. The journal publishes work of the highest standards and importance in all areas of biology and medicine, including Epidemiology and Global Health, and Genetics and Genomics. It receives financial support and strategic guidance from the Howard Hughes Medical Institute, the Knut and Alice Wallenberg Foundation, the Max Planck Society, and Wellcome.
Emily Packer, the Media Relations Manager at eLife, can be reached at [email protected] or at 44 (0)1223 855373.
In a large cohort of Kenyan children diagnosed with severe malaria, the researchers estimate that approximately one-third of the children were misdiagnosed. Many children diagnosed with severe malaria may have other life-threatening infections.
The discovery could help expedite research for better treatments of severe malaria. The researchers hope their new model can be used by other scientists and clinicians to improve the accuracy of diagnosis in children suspected of having severe malaria.
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