Prospective, clinical comparison of self-collected throat-bilateral nares swabs and saline gargle compared to health care provider collected nasopharyngeal swabs among symptomatic outpatients with potential SARS-CoV-2 infection
Bibliographic record
Abstract
Background: In British Columbia (BC), self-collected saline gargle (SG) is the only alternative to health care provider (HCP)-collected nasopharyngeal (NP) swabs to detect SARS-CoV-2 in an outpatient setting by polymerase chain reaction (PCR). However, some individuals cannot perform a SG. Our study aimed to assess combined throat-bilateral nares (TN) swabbing as a swab-based alternative. Methods: Symptomatic individuals greater than 12 years of age seeking a COVID-19 PCR test at one of two COVID-19 collection centres in Metro Vancouver were asked to participate in this study. Participants provided a HCP-collected NP sample and a self-collected SG and TN sample for PCR testing, which were either HCP observed or unobserved. Results: Three-hundred and eleven individuals underwent all three collections. Compared against HCP-NP, SG was 99% sensitive and 98% specific (kappa 0.97) and TN was 99% sensitive and 99% specific (kappa 0.98). Using the final clinical test interpretation as the reference standard, NP was 98% sensitive and 100% specific (kappa 0.98), and both SG and TN were 99% sensitive and 100% specific (both kappa 0.99). Mean cycle threshold values for each viral target were higher in SG specimens compared to the other sample types; however, this did not significantly impact the clinical performance, because the positivity rates were similar. The clinical performance of all specimen types was comparable within the first 7 days of symptom onset, regardless of the observation method. SG self-collections were rated the most acceptable, followed by TN. Conclusions: TN provides another less invasive self-collection modality for symptomatic outpatient SARS-CoV-2 PCR testing.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".