Clinical evaluation of the GeneXpert® Xpert® Xpress SARS-CoV-2/Flu/RSV combination test
Bibliographic record
Abstract
The Cepheid Xpert Xpress SARS-CoV-2/Flu/RSV combination test received emergency use authorization approval by the United States Food and Drug Administration in December 2020, and Health Canada approval in January 2021. The performance characteristics of the GeneXpert Xpert Xpress SARS-CoV-2/Flu/RSV combination test were assessed at Lakeridge Health Oshawa and the National Microbiology Laboratory of Canada. The combination test was compared to the Xpert SARS-CoV-2 and Xpert Flu/RSV assays, and the BioFire FilmArray Respiratory Panel 2.1 (RP2.1) test kit. Materials evaluated were serial dilutions of chemically-inactivated SARS-CoV-2 and remnant clinical specimens (nasal or nasopharyngeal swabs) collected from patients. The limit of detection (LOD) for the SARS-CoV-2 component of the Xpert SARS-CoV-2/Flu/RSV combination test was determined to be <100 viral copies/mL when using chemically-inactivated SARS-CoV-2. In total, 86 clinical positive and 51 clinical negative samples were used for this study, with mixtures of clinical positives being used to mimic coinfection and screen for competitive inhibition. The combination test showed a high percent agreement with the Xpert SARS-CoV-2 and Xpert Flu/RSV tests, as well as the BioFire FilmArray RP2.1. Based on the findings from this study and a growing body of research, the Xpert SARS-CoV-2/Flu/RSV combination test will serve as an effective replacement for the Xpert SARS-CoV-2 and Xpert Flu/RSV assays.
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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 | 0.004 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".