Detection of Plasmodium Infection by the illumigene Malaria Assay Compared to Reference Microscopy and Real-Time PCR
Bibliographic record
Abstract
ABSTRACT Malaria is one of the leading causes of infectious disease in travelers returning from the tropics. The diagnosis of malaria is typically performed by examining Giemsa-stained thick and thin peripheral blood smears, which is time consuming, labor intensive, and requires high levels of proficiency. Alternatively, loop-mediated isothermal amplification (LAMP) is a new molecular method, which is rapid, sensitive, and requires less capital equipment and technological training. We conducted a retrospective study comparing two formats of a commercial LAMP assay (Meridian illumi gene malaria [M] and malaria Plus [MP]) versus reference microscopy on archived blood specimens ( n = 140) obtained from unique returning travelers suspected of having malaria. Discrepant results were resolved by either repeat testing or a laboratory developed ultrasensitive real-time PCR method. On initial testing, the Meridian illumi gene M and MP kits had sensitivities of 97.3% (95% confidence interval [CI], 90.7 to 99.7%) and 100.0% (95.1 to 100.0%) and specificities of 93.8% (84.8 to 98.3%) and 91.5% (81.3 to 97.2%), respectively, versus reference microscopy. We project a significant cost reduction in low prevalence settings where malaria is not endemic with LAMP-based malaria screening given the excellent negative predictive value achieved with LAMP.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".