Throat and nasal swabs for molecular detection of respiratory viruses in acute pharyngitis
Bibliographic record
Abstract
BACKGROUND: Detection of specific respiratory viruses is important for surveillance programs, where nasopharyngeal or nasal swabs have traditionally been used. Our objective was to determine whether sampling with a throat swab provides incremental benefit-when used in conjunction with a nasal swab-to detect respiratory viruses among patients with acute pharyngitis in the outpatient setting. FINDINGS: Among 83 university students with acute pharyngitis, we detected respiratory viruses with molecular assays on two samples collected per student: with a flocked nasal mid-turbinate swab and a rayon throat swab. Forty-eight (58 %) patients had virus-positive samples, with 49 virus positives detected by either swab (one patient had a dual viral co-infection). The most common viruses were rhinovirus, coronavirus, and influenza A virus. Specifically, 29 virus positives were detected by both swabs, 14 exclusively by the nasal swab, and six exclusively by the throat swab. The additional six virus positives detected by the throat swab corresponded to an absolute increase in viral detection of 7.1 % (95 % CI: 1.2-12.9 %); the specific viruses detected were four rhinoviruses and two coronaviruses. CONCLUSIONS: The flocked nasal swab samples respiratory viruses well, even among patients whose primary complaint is a sore throat. The rayon throat swab has modest incremental value over and above using the flocked nasal mid-turbinate swab alone, which suggests that while throat swabs alone would not be adequate for respiratory viral surveillance, they may have value as a supplementary test.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".