Comparison of saliva with oral and nasopharyngeal swabs for SARS‐CoV‐2 detection on various commercial and laboratory‐developed assays
Bibliographic record
Abstract
Abstract The accurate laboratory detection of the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is a crucial element in the fight against coronavirus disease 2019 (COVID‐19). Reverse transcription‐polymerase chain reaction testing on combined oral and nasopharyngeal swab (ONPS) suffers from several limitations, including the need for qualified personnel, the discomfort caused by invasive nasopharyngeal sample collection, and the possibility of swab and transport media shortage. Testing on saliva would represent an advancement. The aim of this study was to compare the concordance between saliva samples and ONPS for the detection of SARS‐CoV‐2 on various commercial and laboratory‐developed tests (LDT). Individuals were recruited from eight institutions in Quebec, Canada, if they had SARS‐CoV‐2 RNA detected on a recently collected ONPS, and accepted to provide another ONPS, paired with saliva. Assays available in the different laboratories (Abbott RealTime SARS‐CoV‐2, Cobas® SARS‐CoV‐2, Simplexa™ COVID‐19 Direct, Allplex™ 2019‐nCoV, RIDA®GENE SARS‐CoV‐2, and an LDT preceded by three different extraction methods) were used to determine the concordance between saliva and ONPS results. Overall, 320 tests were run from a total of 125 saliva and ONPS sample pairs. All assays yielded similar sensitivity when saliva was compared to ONPS, with the exception of one LDT (67% vs. 93%). The mean difference in cycle threshold (∆ C t ) was generally (but not significantly) in favor of the ONPS for all nucleic acid amplification tests. The maximum mean ∆ C t was 2.0, while individual ∆ C t varied importantly from −17.5 to 12.4. Saliva seems to be associated with sensitivity similar to ONPS for the detection of SARS‐CoV‐2 by various assays.
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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 | 0.001 | 0.002 |
| 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".