Detection of SARS-CoV-2 from Saliva as Compared to Nasopharyngeal Swabs in Outpatients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Widely available and easily accessible testing for COVID-19 is a cornerstone of pandemic containment strategies. Nasopharyngeal swabs (NPS) are the currently accepted standard for sample collection but are limited by their need for collection devices and sampling by trained healthcare professionals. The aim of this study was to compare the performance of saliva to NPS in an outpatient setting. This was a prospective study conducted at three centers, which compared the performance of saliva and NPS samples collected at the time of assessment center visit. Samples were tested by real-time reverse transcription polymerase chain reaction and sensitivity and overall agreement determined between saliva and NPS. Clinical data was abstracted by chart review for select study participants. Of the 432 paired samples, 46 were positive for SARS-CoV-2, with seven discordant observed between the two sample types (four individuals testing positive only by NPS and three by saliva only). The observed agreement was 98.4% (kappa coefficient 0.91) and a composite reference standard demonstrated sensitivity of 0.91 and 0.93 for saliva and NPS samples, respectively. On average, the Ct values obtained from saliva as compared to NPS were higher by 2.76. This study demonstrates that saliva performs comparably to NPS for the detection of SARS-CoV-2. Saliva was simple to collect, did not require transport media, and could be tested with equipment readily available at most laboratories. The use of saliva as an acceptable alternative to NPS could support the use of widespread surveillance testing for SARS-CoV-2.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 it