Swish and gargle saliva sampling is a patient-friendly and comparable alternative to nasopharyngeal swabs to detect SARS-CoV-2 in outpatient settings for adults and children
Bibliographic record
Abstract
ABSTRACT Nasopharyngeal swabs (NPS) are considered the standard specimen for SARS-CoV-2 detection by PCR. We aimed to compare detection performance and patient experience of NPS with swish and gargle saliva (SGS) to determine its potential as an accurate, easy-to-collect, and comfortable alternative. We conducted a prospective study from March to May 2021 and recruited pediatric and adult outpatients seeking COVID-19 testing. Paired NPS and 5-mL SGS were collected from each participant during the same visit and tested in parallel using validated rRT-PCR assays. Variant of concern (VOC) analysis was performed for positive NPS specimens. The participant completed the surveys regarding their experience with the two collection methods. We included 238 participants in the SARS-CoV-2 detection performance analysis. Thirty-two participants tested positive for both NPS and SGS. In comparison to NPS, the sensitivity and specificity of SGS to detect SARS-CoV-2 were 94.1% (95%CI; 80.3%–99.3%) and 97.1% (95%CI; 93.7%–98.9%), respectively. Six participants tested positive only with SGS and only two with NPS. NPS is an imperfect gold standard. Thus, when compared to the COVID-19 case, that is, a patient with positive NPS and/or SGS, the sensitivity for NPS and SGS were 85.0% and 95.0%, respectively. VOC results ( n = 26) revealed that 92% of the cases were alpha. From the 238 surveys, 89.9% of the participants described SGS collection as comfortable or very comfortable compared to 15.1% for NPS; 90.2% of the participants were likely or very likely to return for SGS collection compared to 59.3% for NPS. SGS is an alternative to NPS for SARS-CoV-2 detection in adult and pediatric outpatients as it is more patient-friendly while still maintaining comparable performance. IMPORTANCE Widespread and frequent testing for COVID-19 was an important strategy to identify infected patients to isolate and control the spread of the disease during the pandemic. The nasopharyngeal swab (NPS) global supply chain and access to trained healthcare professionals for standard NPS collection were often compromised. Patient discomfort and limited access challenged health systems to reach large numbers for testing in adult and pediatric populations. Our study revealed that swish and gargle saliva (SGS) was comparable to NPS in detecting SARS-CoV-2 and more patient-friendly than NPS. Patients were more likely to repeat the test with SGS. SGS was amenable to self-collection instead of relying on skilled professionals. This comprehensive evaluation highlights the challenges of comparing the accuracy of new methods to imperfect gold standards and identifies additional patient-centric factors that should be considered when defining such standards. Thus, SGS is an advantageous alternative specimen collection for outpatient en masse testing.
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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 | 0.000 | 0.000 |
| 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 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".