Multiplex real-time quantitative PCR, microscopy and rapid diagnostic immuno-chromatographic tests for the detection of Plasmodium spp: performance, limit of detection analysis and quality assurance
Bibliographic record
Abstract
BACKGROUND: Accurate laboratory diagnosis of malaria species in returning travelers is paramount in the treatment of this potentially fatal infectious disease. MATERIALS AND METHODS: A total of 466 blood specimens from returning travelers to Africa, Asia, and South/Central America with suspected malaria infection were collected between 2007 and 2009 at the reference public health laboratory. These specimens were assessed by reference microscopy, multipex real-time quantitative polymerase chain reaction (QPCR), and two rapid diagnostic immuno-chromatographic tests (ICT) in a blinded manner. Key clinical laboratory parameters such as limit of detection (LOD) analysis on clinical specimens by parasite stage, inter-reader variability of ICTs, staffing implications, quality assurance and cost analysis were evaluated. RESULTS: QPCR is the most analytically sensitive method (sensitivity 99.41%), followed by CARESTART (sensitivity 88.24%), and BINAXNOW (sensitivity 86.47%) for the diagnosis of malaria in returning travelers when compared to reference microscopy. However, microscopy was unable to specifically identify Plasmodia spp. in 18 out of 170 positive samples by QPCR. Moreover, the 17 samples that were negative by microscopy and positive by QPCR were also positive by ICTs. Quality assurance was achieved for QPCR by exchanging a blinded proficiency panel with another reference laboratory. The Kappa value of inter-reader variability among three readers for BINAXNOW and CARESTART was calculated to be 0.872 and 0.898 respectively. Serial dilution studies demonstrated that the QPCR cycle threshold correlates linearly with parasitemia (R(2) = 0.9746) in a clinically relevant dynamic range and retains a LOD of 11 rDNA copies/microl for P. falciparum, which was several log lower than reference microscopy and ICTs. LOD for QPCR is affected not only by parasitemia but the parasite stage distribution of each clinical specimen. QPCR was approximately 6-fold more costly than reference microscopy. DISCUSSION: These data suggest that multiplex QPCR although more costly confers a significant diagnostic advantage in terms of LOD compared to reference microscopy and ICTs for all four species. Quality assurance of QPCR is essential to the maintenance of proficiency in the clinical laboratory. ICTs showed good concordance between readers however lacked sensitivity for non-falciparum species due to antigenic differences and low parasitemia. CONCLUSION: Multiplex QPCR but not ICTs is an essential adjunct to microscopy in the reference laboratory detection of malaria species specifically due to the superior LOD. ICTs are better suited to the non-reference laboratory where lower specimen volumes challenge microscopy proficiency in the non-endemic setting.
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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 | 0.022 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".