Acceptable performance of the Abbott ID NOW among symptomatic individuals with confirmed COVID-19
Bibliographic record
Abstract
Introduction. The ID NOW is FDA approved for the detection of SARS-CoV-2 in symptomatic individuals within the first 7 days of symptom onset for COVID-19 if tested within 1 h of specimen collection. Gap statement. Clinical data on the performance of the ID NOW are limited, with many studies varying in their study design and/or having small sample size. Aim. In this study we aimed to determine the clinical performance of the ID NOW compared to conventional RT-PCR testing. Methodology. Adults with COVID-19 in the community or hospital were recruited into the study. Paired throat swabs were collected, with one throat swab transported immediately in an empty sterile tube to the laboratory for ID NOW testing, and the other transported in universal transport media and tested by an in-house SARS-CoV-2 RT-PCR assay targeting the E gene. Results. In total, 133 individuals were included in the study; 129 samples were positive on either the ID NOW and/or RT-PCR. Assuming any positive result on either assay represents a true positive, positive per cent agreement (PPA) of the ID NOW compared to RT-PCR with 95 % confidence intervals was 89.1 % (82.0–94.1%) and 91.6 % (85.1–95.9%), respectively. When analysing individuals with symptom duration ≤7 days and who had the ID NOW performed within 1 h ( n =62), ID NOW PPA increased to 98.2 %. Conclusion. Results from the ID NOW were reliable, especially when adhering to the manufacturer’s recommendations for testing.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 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".