Salivary testing for SARS-CoV-2 in the pediatric population: a diagnostic accuracy study
Bibliographic record
Abstract
BACKGROUND: Accurate and timely testing for SARS-CoV-2 in the pediatric population is crucial to control the COVID-19 pandemic; saliva testing has been proposed as a less invasive alternative to nasopharyngeal swabs. We sought to compare the detection of SARS-CoV-2 using saliva versus nasopharyngeal swab in the pediatric population, and to determine the optimum time of testing for SARS-CoV-2 using saliva. METHODS: We conducted a longitudinal diagnostic study in Ottawa, Canada, from Jan. 19 to Mar. 26, 2021. Children aged 3-17 years were eligible if they exhibited symptoms of COVID-19, had been identified as a high-risk or close contact to someone confirmed positive for SARS-CoV-2 or had travelled outside Canada in the previous 14 days. Participants provided both nasopharyngeal swab and saliva samples. Saliva was collected using a self-collection kit (DNA Genotek, OM-505) or a sponge-based kit (DNA Genotek, ORE-100) if they could not provide a saliva sample into a tube. RESULTS: Among 1580 paired nasopharyngeal and saliva tests, 60 paired samples were positive for SARS-CoV-2. Forty-four (73.3%) were concordant-positive results and 16 (26.6%) were discordant, among which 8 were positive only on nasopharyngeal swab and 8 were positive only on saliva testing. The sensitivity of saliva was 84.6% (95% confidence interval 71.9%-93.1%). INTERPRETATION: Salivary testing for SARS-CoV-2 in the pediatric population is less invasive and shows similar detection of SARS-CoV-2 to nasopharyngeal swabs. It may therefore provide a feasible alternative for diagnosis of SARS-CoV-2 infection in children.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".