Evaluation of Commercially Available Diagnostic Tests for the Detection of Dengue Virus NS1 Antigen and Anti-Dengue Virus IgM Antibody
Bibliographic record
Abstract
Commercially available diagnostic test kits for detection of dengue virus (DENV) non-structural protein 1 (NS1) and anti-DENV IgM were evaluated for their sensitivity and specificity and other performance characteristics by a diagnostic laboratory network developed by World Health Organization (WHO), the UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR) and the Pediatric Dengue Vaccine Initiative (PDVI). Each network laboratory contributed characterized serum specimens for the panels used in the evaluation. Microplate enzyme-linked immunosorbent assay (ELISA) and rapid diagnostic test (RDT formats) were represented by the kits. Each ELISA was evaluated by 2 laboratories and RDTs were evaluated by at least 3 laboratories. The reference tests for IgM anti-DENV were laboratory developed assays produced by the Armed Forces Research Institute for Medical Science (AFRIMS) and the Centers for Disease Control and Prevention (CDC), and the NS1 reference test was reverse transcriptase polymerase chain reaction (RT-PCR). Results were analyzed to determine sensitivity, specificity, inter-laboratory and inter-reader agreement, lot-to-lot variation and ease-of-use. NS1 ELISA sensitivity was 60-75% and specificity 71-80%; NS1 RDT sensitivity was 38-71% and specificity 76-80%; the IgM anti-DENV RDTs sensitivity was 30-96%, with a specificity of 86-92%, and IgM anti-DENV ELISA sensitivity was 96-98% and specificity 78-91%. NS1 tests were generally more sensitive in specimens from the acute phase of dengue and in primary DENV infection, whereas IgM anti-DENV tests were less sensitive in secondary DENV infections. The reproducibility of the NS1 RDTs ranged from 92-99% and the IgM anti-DENV RDTs from 88-94%.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".