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Since the introduction of Giemsa stain in 1904 until today, malaria microscopy has been the standard of practice for malaria diagnosis. However, microscopic detection of malaria parasites is labour-intensive, time-consuming and expertise-demanding. Moreover, the slide interpretation is highly dependent on the staining technique and the technician's expertise.
To address these, multiple organisations have developed next generation microscopes to move towards a next generation microscope that can improve slide preparation, interpretation or data collection, or a combination of these features.
In this study, a prospective evaluation of miLabâ„¢ and other next generation automated microscope solutions as well as a malaria rapid diagnostic test (RDT) reader app will be performed in malaria-endemic countries to assess their clinical performance for detection of malaria clinical cases at POC.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Case | Symptomatic patients positive for malaria by PCR |
| |
| Control | Symptomatic patients negative for malaria by PCR |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Novel malaria diagnostics & tools | Diagnostic Test | Next generation microscopy tools for malaria diagnosis and medical applications |
|
| Measure | Description | Time Frame |
|---|---|---|
| Clinical performance assessment | Point estimates of clinical performance characteristics with 95% confidence intervals (sensitivity, specificity) of next generation microscopy tools using nPCR as the reference test for the detection of malaria clinical cases | up to 6 months |
| Concordance | Point estimate with 95% confidence intervals of the percentage agreement in interpreting malaria diagnostics between the app and visual reading | up to 6 months |
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Inclusion Criteria:
Exclusion Criteria:
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Patients with symptoms suggestive of malaria seeking clinical care in health facilities
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Institute of Endemic Diseases, Medical Campus | Khartoum | Sudan |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 38943203 | Derived | Hamid MMA, Mohamed AO, Mohammed FO, Elaagip A, Mustafa SA, Elfaki T, Jebreel WMA, Albsheer MM, Dittrich S, Owusu EDA, Yerlikaya S. Diagnostic accuracy of an automated microscope solution (miLab) in detecting malaria parasites in symptomatic patients at point-of-care in Sudan: a case-control study. Malar J. 2024 Jun 28;23(1):200. doi: 10.1186/s12936-024-05029-3. |
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| ID | Term |
|---|---|
| D008288 | Malaria |
| ID | Term |
|---|---|
| D011528 | Protozoan Infections |
| D010272 | Parasitic Diseases |
| D007239 | Infections |
| D000096724 | Mosquito-Borne Diseases |
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| D000079426 |
| Vector Borne Diseases |