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Comparison of Saliva and Nasopharyngeal Swab Nucleic Acid Amplification Testing for Detection of SARS-CoV-2

2021· review· en· W3119343341 on OpenAlexaff
Guillaume Butler‐Laporte, Alexander Lawandi, Ian Schiller, Mandy Yao, Nandini Dendukuri, Emily G. McDonald, Todd C. Lee

Bibliographic record

VenueJAMA Internal Medicine · 2021
Typereview
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsMcGill UniversityMcGill University Health CentreRoyal Victoria Regional Health CentreRoyal Victoria Hospital
Fundersnot available
KeywordsMedicineMeta-analysisNucleic Acid Amplification TestsMEDLINEInternal medicineVirology

Abstract

fetched live from OpenAlex

Importance: Nasopharyngeal swab nucleic acid amplification testing (NAAT) is the noninvasive criterion standard for diagnosis of coronavirus disease 2019 (COVID-19). However, it requires trained personnel, limiting its availability. Saliva NAAT represents an attractive alternative, but its diagnostic performance is unclear. Objective: To assess the diagnostic accuracy of saliva NAAT for COVID-19. Data Sources: In this systematic review, a search of the MEDLINE and medRxiv databases was conducted on August 29, 2020, to find studies of diagnostic test accuracy. The final meta-analysis was performed on November 17, 2020. Study Selection: Studies needed to provide enough data to measure salivary NAAT sensitivity and specificity compared with imperfect nasopharyngeal swab NAAT as a reference test. An imperfect reference test does not perfectly reflect the truth (ie, it can give false results). Studies were excluded if the sample contained fewer than 20 participants or was neither random nor consecutive. The Quality Assessment of Diagnostic Accuracy Studies 2 tool was used to assess the risk of bias. Data Extraction and Synthesis: Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guideline was followed for the systematic review, with multiple authors involved at each stage of the review. To account for the imperfect reference test sensitivity, we used a bayesian latent class bivariate model for the meta-analysis. Main Outcomes and Measures: The primary outcome was pooled sensitivity and specificity. Two secondary analyses were performed: one restricted to peer-reviewed studies, and a post hoc analysis limited to ambulatory settings. Results: The search strategy yielded 385 references, and 16 unique studies were identified for quantitative synthesis. Eight peer-reviewed studies and 8 preprints were included in the meta-analyses (5922 unique patients). There was significant variability in patient selection, study design, and stage of illness at which patients were enrolled. Fifteen studies included ambulatory patients, and 9 exclusively enrolled from an outpatient population with mild or no symptoms. In the primary analysis, the saliva NAAT pooled sensitivity was 83.2% (95% credible interval [CrI], 74.7%-91.4%) and the pooled specificity was 99.2% (95% CrI, 98.2%-99.8%). The nasopharyngeal swab NAAT had a sensitivity of 84.8% (95% CrI, 76.8%-92.4%) and a specificity of 98.9% (95% CrI, 97.4%-99.8%). Results were similar in secondary analyses. Conclusions and Relevance: These results suggest that saliva NAAT diagnostic accuracy is similar to that of nasopharyngeal swab NAAT, especially in the ambulatory setting. These findings support larger-scale research on the use of saliva NAAT as an alternative to nasopharyngeal swabs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.143
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.034
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.143
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0110.025
Bibliometrics0.0050.004
Science and technology studies0.0000.001
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.205
GPT teacher head0.439
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

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Citations328
Published2021
Admission routes1
Has abstractyes

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