<scp>COVID</scp>‐19 rapid antigen tests approved for self‐testing in Australia: published diagnostic test accuracy studies and manufacturer‐supplied information. A systematic review
Bibliographic record
Abstract
OBJECTIVES: To review evaluations of the diagnostic accuracy of coronavirus disease 2019 (COVID-19) rapid antigen tests (RATs) approved by the Therapeutic Goods Administration (TGA) for self-testing by ambulatory people in Australia; to compare these estimates with values reported by test manufacturers. STUDY DESIGN: Systematic review of publications in any language that reported cross-sectional, case-control, or cohort studies in which the participants were ambulatory people in the community or health care workers in hospitals in whom severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection was suspected, and the results of testing self-collected biological samples with a TGA-approved COVID-19 RAT were compared with those of reverse transcription-polymerase chain reaction (RT-PCR) testing for SARS-CoV-2. Estimates of diagnostic accuracy (sensitivity, specificity) were checked and compared with manufacturer estimates published on the TGA website. DATA SOURCES: Publications (to 1 September 2022) identified in the Cochrane COVID-19 Study Register and the World Health Organization COVID-19 research database. Information on manufacturer diagnostic accuracy evaluations was obtained from the TGA website. DATA SYNTHESIS: Twelve publications that reported a total of eighteen evaluations of eight RATs approved by the TGA for self-testing (manufacturers: All Test, Roche, Flowflex, MP Biomedicals, Clungene, Panbio, V-Chek, Whistling) were identified. Five studies were undertaken in the Netherlands, two each in Germany and the United States, and one each in Denmark, Belgium, and Canada; test sample collection was unsupervised in twelve studies, and supervised by health care workers or researchers in six. Estimated sensitivity with unsupervised sample collection ranged from 20.9% (MP Biomedicals) to 74.3% (Roche), and with supervised collection from 7.7% (V-Chek) to 84.4% (Panbio); the estimates were between 8.2 and 88 percentage points lower than the values reported by the manufacturers. Test specificity was high for all RATs (97.9-100%). CONCLUSIONS: The risk of false negative results when using COVID-19 RATs for self-testing may be considerably higher than apparent in manufacturer reports on the TGA website, with implications for the reliability of these tests for ruling out infection.
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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 | 0.018 | 0.119 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".