Validation of saliva sampling as an alternative to oro-nasopharyngeal swab for detection of SARS-CoV-2 using unextracted rRT-PCR with the Allplex 2019-nCoV assay
Bibliographic record
Abstract
Introduction. The current severe acute respiratory syndrome-associated coronavirus-2 (SARS-CoV-2) pandemic has stressed the global supply chain for specialized equipment, including flocked swabs. Hypothesis. Saliva could be a potential alternative specimen source for diagnosis of SARS-CoV-2 infection by reverse-transcriptase PCR (RT-PCR). Aim. To compare the detection efficiency of SARS-CoV-2 RNA in saliva and oro-nasopharyngeal swab (ONPS) specimens. Methodology. Patients recruited from hospital provided paired saliva and ONPS specimens. We performed manual or automated RT-PCR with prior proteinase K treatment without RNA extraction using the Seegene Allplex 2019 nCoV assay. Results. Of the 773 specimen pairs, 165 (21.3 %) had at least one positive sample. Additionally, 138 specimens tested positive by both sampling methods. Fifteen and 12 cases were detected only by nasopharyngeal swab and saliva, respectively. The sensitivity of ONPS (153/165; 92.7 %; 95 % CI: 88.8–96.7) was similar to that of saliva (150/165; 90.9 %; 95 % CI: 86.5–95.3; P =0.5). In patients with symptoms for ≤ 10 days, the sensitivity of ONPS (118/126; 93.7 %; 95 % CI: 89.4–97.9) was similar to that of saliva (122/126; 96.8 %; 95 % CI: 93.8–99.9 %; P =0.9). However, the sensitivity of ONPS (20/22; 95.2 %; 95 % CI: 86.1–100) was higher than that of saliva (16/22; 71.4 %; 95 % CI: 52.1–90.8) in patients with symptoms for more than 10 days. Conclusions. Saliva sampling is an acceptable alternative to ONPS for diagnosing SARS-CoV-2 infection in symptomatic individuals displaying symptoms for ≤ 10 days. These results reinforce the need to expand the use of saliva samples, which are self-collected and do not require swabs.
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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 | 0.002 | 0.003 |
| 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".