One swab, two tests: Validation of dual SARS-CoV-2 testing on the Abbott ID NOW™
Bibliographic record
Abstract
BACKGROUND: Point-of-care tests (POCT) are promising tools to detect SARS-CoV-2 in specific settings. Initial reports suggest the ID NOW™ COVID-19 assay (Abbott Diagnostics Inc, USA) is less sensitive than standard real-time reverse transcription polymerase chain reaction (rRT-PCR) assays. This has raised concern over false negatives in SARS-CoV-2 POCT. OBJECTIVES: We compared the performance of the ID NOW™ COVID-19 assay to our in-house rRT-PCR assay to assess whether dry swabs used in ID NOW™ testing could be stored in transport media and be re-tested by rRT-PCR for redundancy and to provide material for further investigation. METHODS: Paired respiratory swabs collected from patients at three acute care hospitals were used. One swab in transport media (McMaster Molecular Media (MMM)) was tested for SARS-CoV-2 by a laboratory-developed two-target rRT-PCR assay. The second was stored dry in a sterile container and tested by the ID NOW™ COVID-19 assay. Following ID NOW™ testing, dry swabs were stored in MMM for up to 48 h and re-tested by rRT-PCR. Serially diluted SARS-CoV-2 particles were used to assess the impact of heat inactivation and storage time. RESULTS: Respiratory swabs (n = 343) from 179 individuals were included. Using rRT-PCR results as the comparator, the ID NOW™ COVID-19 assay had positive (PPA) and negative (NPA) percent agreements of 87.0% (95% CI:0.74-0.94) and 99.7% (95% CI:0.98-0.99). Re-tested swabs placed in MMM following ID NOW testing had PPA and NPA of 88.8% (95% CI:0.76-0.95) and 99.7% (95% CI:0.98-0.99), respectively. CONCLUSIONS: Storing spent dry swabs in transport media for redundancy rRT-PCR testing is a potential approach to address possible false negatives with the ID NOW™ COVID-19 assay.
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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 | 0.003 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".