Comparison of the Luminex xTAG Respiratory Viral Panel with In-House Nucleic Acid Amplification Tests for Diagnosis of Respiratory Virus Infections
Bibliographic record
Abstract
Detection of respiratory viruses using sensitive real-time nucleic acid amplification tests (NATs) is invaluable for patient and outbreak management. However, the wide range of potential respiratory virus pathogens makes testing using individual real-time NATs expensive and laborious. The objective of this study was to compare the detection of respiratory virus targets using the Luminex xTAG respiratory viral panel (RVP) assay with individual real-time NATs used at the Provincial Laboratory of Public Health, Calgary, Alberta, Canada. The study included 1,530 specimens submitted for diagnosis of respiratory infections from December 2006 to May 2007. Direct-fluorescent-antigen-positive nasopharyngeal samples were excluded from this study. A total of 690 and 643 positives were detected by RVP and in-house NATs, respectively. Kappa correlation between in-house NATs and RVP for all targets ranged from 0.721 to 1.000. The majority of specimens missed by in-house NATs (96.7%) were positive for picornaviruses. Samples missed by RVP were mainly positive for adenovirus (51.7%) or respiratory syncytial virus (27.5%) by in-house NATs and in general had low viral loads. RVP allows for multiplex detection of 20 (and differentiation between 19) respiratory virus targets with considerable time and cost savings compared with alternative NATs. Although this first version of the RVP assay has lower sensitivity than in-house NATs for detection of adenovirus, it has good sensitivity for other targets. The identification of picornaviruses and coronaviruses and concurrent typing of influenza A virus by RVP, which are not currently included in our diagnostic testing algorithm, will improve our diagnosis of respiratory tract infections.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".