Relevance of reviewing endpoint analysis for negative results on the Xpert Xpress Flu/RSV
Bibliographic record
Abstract
After the implementation of the Xpert Xpress Flu/respiratory syncytial virus (RSV) assay for rapid respiratory molecular testing, we investigated the significance of reported endpoint values for influenza A, influenza B, and RSV). This study prospectively analyzed nasopharyngeal swabs submitted to our virology laboratory in the 2018/19 influenza season. Initial testing was performed on the Xpress Flu/RSV assay. Samples were further tested on a laboratory-developed multiplex polymerase chain reaction (laboratory-developed multiplex respiratory test [LDT]) if the sample was reported as negative by the Xpress Flu/RSV but had an elevated endpoint value ≥5 for any respiratory virus target. There were 1040 negative results on the Xpress Flu/RSV; thirty-one had at least one endpoint value ≥5 [influenza A (25), influenza B (1), RSV (2), influenza A/RSV (1), and influenza A/B/RSV (2)]. Five samples (5/31, 16.1%) were positive on the LDT for influenza A or RSV. In contrast, the positivity rate on the LDT for negative Xpress Flu/RSV samples with endpoint values less than 5 was 0.35% (P < .0001). A threshold for endpoint values could not reliably be established to differentiate a potential influenza A positive result from a negative result on the LDT. Routine evaluation ofendpoint values should be a consideration for laboratories implementing Xpress Flu/RSV, in addition to supplementary respiratory virus testing for clinically relevant situations.
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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 | 0.084 | 0.170 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".