Clinical performance of SARS-CoV-2 detection on the cobas Liat using water gargle samples
Bibliographic record
Abstract
Spring water gargle (SWG) is a suitable, non-invasive, alternative specimen for SARS-CoV-2 detection by RT-PCR. This study sought to evaluate the performance of the cobas Liat point-of-care system for the detection of SARS-CoV-2 in SWG samples. SWG samples and standard oral and nasopharyngeal swab (ONPS) were collected simultaneously from participants in a COVID-19 screening clinic, in November and December 2020. Both sample types were analyzed in parallel on the cobas Liat platform and with the Seegene Allplex 2019-nCoV assay. Among the 110 participants, 53% had compatible symptoms and 71% had a contact with a confirmed COVID-19 case. Only two (1.8%) individuals had neither symptoms nor contact. Amongst 110 paired samples, 25 (23%) were positive for SARS-CoV-2 on the cobas Liat for a least one sample type, with a kappa coefficient of 0.92. Agreement between the cobas Liat platform and the Seegene assay was also excellent (kappa coefficient values of 0.94 and 0.95). Two SWG samples failed to provide a positive result when their ONPS pair was positive, but their cycle threshold (Ct) values were >35 on the Seegene assay, reflecting a low viral load. Overall, the performance of the cobas Liat platform is excellent for the detection of SARS-CoV-2 in SWG samples in a high pre-test probability population.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.002 |
| 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".