Use of a three-band HRP2/pLDH combination rapid diagnostic test increases diagnostic specificity for falciparum malaria in Ugandan children
Bibliographic record
Abstract
BACKGROUND: Rapid diagnostic tests (RDTs) for malaria provide a practical alternative to light microscopy for malaria diagnosis in resource-limited settings. Three-band RDTs incorporating two parasite antigens may have enhanced diagnostic specificity, relative to two-band RDTs with a single parasite antigen (typically histidine-rich protein 2 [HRP2]). METHODS: Phase 1: 2,000 children, two months to five years of age, admitted to a referral hospital in Jinja, Uganda, with acute febrile illness were enrolled. A WHO highly rated three-band RDT was compared to light microscopy of thick peripheral blood films read by local expert microscopists.Phase 2: the three-band RDT was used as a screening tool for inclusion of patients in a clinical trial, and subjects with three positive RDT bands were tested by microscopy using blood samples drawn in parallel. Discordant results were adjudicated by PCR. RESULTS: Phase 1: 1,648 children had both a RDT and peripheral blood smear performed. The specificity of a RDT with all three bands positive was 82% (95% CI: 79-85%) compared to 62% (95% CI: 59-66%) for HRP2 alone. The sensitivity was 88% (95% CI: 85-89%) and 94% (95% CI: 92-95%) for three-band positive RDT and HRP2 antigen, respectively. 119 patients (7.2%) had a positive HRP2 band, but negative parasite lactate dehydrogenase (pLHD) band and negative peripheral smear, and 72 (61%) of these had received pre-treatment with anti-malarials, suggesting a false positive HRP2 result (p = 0.002).Phase 2: the positive predictive value (PPV) of the three-band RDT was 94% (95% CI 89%-97%) using microscopy as the reference standard. However, microscopy-discordant results were shown to be positive for P. falciparum by PCR in all cases, suggesting that the PPV was in fact higher. CONCLUSION: The pLDH antigen on three-band RDTs, used in combination with HRP2, provides added diagnostic specificity for malaria parasitaemia and may be useful to distinguish acute infection from recently treated infection. In situations where diagnostic specificity is desirable (e.g., for selection of malaria-infected participants in clinical trials), a three-band RDT should be considered in a sub-Saharan African 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 | 0.003 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".