Evaluation of a Dengue NS1 Antigen Detection Assay Sensitivity and Specificity for the Diagnosis of Acute Dengue Virus Infection
Bibliographic record
Abstract
BACKGROUND: Currently, no dengue NS1 detection kit has regulatory approval for the diagnosis of acute dengue fever. Here we report the sensitivity and specificity of the InBios DEN Detect NS1 ELISA using a panel of well characterized human acute fever serum specimens. METHODOLOGY/PRINCIPAL FINDINGS: The InBios DENV Detect NS1 ELISA was tested using a panel composed of 334 serum specimens collected from acute febrile patients seeking care in a Bangkok hospital in 2010 and 2011. Of these patients, 314 were found to have acute dengue by either RT-PCR and/or anti-dengue IgM/IgG ELISA. Alongside the InBios NS1 ELISA kit, we compared the performance characteristics of the BioRad Platelia NS1 antigen kit. The InBios NS1 ELISA Ag kit had a higher overall sensitivity (86% vs 72.8%) but equal specificity (100%) compared to the BioRad Platelia kit. The serological status of the patient significantly influenced the outcome. In primary infections, the InBios NS1 kit demonstrated a higher sensitivity (98.8%) than in secondary infections (83.5%). We found significant variation in the sensitivity of the InBios NS1 ELISA kit depending on the serotype of the dengue virus and also found decreasing sensitivity the longer after the onset of illness, showing 100% sensitivity early during illness, but dropping below 50% by Day 7. CONCLUSION/SIGNIFICANCE: The InBios NS1 ELISA kit demonstrated high accuracy when compared to the initial clinical diagnosis with greater than 85% agreement when patients were clinically diagnosed with dengue illness. Results presented here suggest the accurate detection of circulating dengue NS1 by the InBios DENV Detect NS1 ELISA can provide clinicians with a useful tool for diagnosis of early dengue infections.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".