Field evaluation of an automated RDT reader and data management device for Plasmodium falciparum/Plasmodium vivax malaria in endemic areas of Colombia
Bibliographic record
Abstract
BACKGROUND: Massive implementation of malaria diagnostics in low-resource countries is regarded as a pivotal strategy in control and elimination efforts. Although malaria rapid diagnostic tests (RDTs) are considered a viable alternative, there are still obstacles to the widespread implementation of this strategy, such as reporting constraints and lack of proper quality assurance of RDT-based programmes at point-of-care (POC). METHODS: A prospective cohort of patients, seeking routine care for febrile episodes at health centres in malaria-endemic areas of Colombia, was used to assess the diagnostic performance of a device based on smartphone technology (Deki ReaderTM, former codename "GenZero"), that assists users at POC to process RDTs. After informed consent, patients were enrolled into the study and blood samples were collected for thick blood smear (TBS) and RDT. The RDT results were interpreted by both visual inspection and Deki Reader device and concordance between visual and device interpretation was measured. Microscopy corrected by real-time polymerase chain reaction (PCR) and microscopy were "gold standard" tests to assess the diagnostic performance. RESULTS: In total, 1,807 patients were enrolled at seven health centres in malaria-endemic areas of Colombia. Thirty-three Plasmodium falciparum and 100 Plasmodium vivax cases were positive by corrected microscopy. Both sensitivity and specificity were 93.9% (95% CI 69.7-95.2) and 98.7% (95% CI 98.5-99.4) for P. falciparum, and 98.0% (95% CI 90.3-98.9) and 97.9% (95% CI 97.1-98.5) for P. vivax. Percentage concordance between visual and device interpretation of RDT was 98.5% and 99.0% for P. vivax and P. falciparum, respectively.The RDT, when compared to TBS, showed high sensitivity and specificity for P. falciparum in both visual and device interpretation, and good overall diagnostic performance for P. vivax. Comparison between PCR as gold standard and visual and device interpretation showed acceptable overall performance for both species. CONCLUSIONS: The diagnostic performance of the Deki Reader was comparable to visual interpretation of RDTs (without significant differences) for both malaria species. Providing standardized automated interpretation of RDTs at POC in remote areas, in addition to almost real-time reporting of cases and enabling quality control would greatly benefit large-scale implementation of RDT-based malaria diagnostic programmes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".