Simplified molecular diagnosis of visceral leishmaniasis: Laboratory evaluation of miniature direct-on-blood PCR nucleic acid lateral flow immunoassay
Bibliographic record
Abstract
BACKGROUND: Diagnosis of visceral leishmaniasis (VL) in resource-limited endemic regions is currently based on serological testing with rK39 immunochromatographic tests (ICTs). However, rK39 ICT frequently has suboptimal diagnostic accuracy. Furthermore, treatment monitoring and detection of VL relapses is reliant on insensitive and highly invasive tissue aspirate microscopy. Miniature direct-on-blood PCR nucleic acid lateral flow immunoassay (mini-dbPCR-NALFIA) is an innovative and user-friendly molecular tool which does not require DNA extraction and uses a lateral flow strip for result read-out. This assay could be an interesting candidate for more reliable VL diagnosis and safer test of cure at the point of care. METHODOLOGY/PRINCIPLE FINDINGS: The performance of mini-dbPCR-NALFIA for diagnosis of VL in blood was assessed in a laboratory evaluation and compared with the accuracy of rK39 ICTs Kalazar Detect in Spain and IT LEISH in East Africa. Limit of detection of mini-dbPCR-NALFIA was 650 and 500 parasites per mL of blood for Leishmania donovani and Leishmania infantum, respectively. In 146 blood samples from VL-suspected patients from Spain, mini-dbPCR-NALFIA had a sensitivity of 95.8% and specificity 97.2%, while Kalazar Detect had a sensitivity of 71.2% and specificity of 94.5%, compared to a nested PCR reference. For a sample set from 58 VL patients, 10 malaria patients and 68 healthy controls from Ethiopia and Kenya, mini-dbPCR-NALFIA had a pooled sensitivity of 87.9% and pooled specificity of 100% using quantitative PCR as reference standard. IT LEISH sensitivity and specificity in the East African samples were 87.9% and 97.4%, respectively. CONCLUSIONS/SIGNIFICANCE: Mini-dbPCR-NALFIA is a promising tool for simplified molecular diagnosis of VL and follow-up of treated patients in blood samples. Future studies should evaluate its use in endemic, resource-limited settings, where mini-dbPCR-NALFIA may provide an accurate and versatile alternative to rK39 ICTs and aspirate microscopy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".