SalivaDirect: an alternative to a conventional RNA extraction protocol for molecular detection of SARS-CoV-2 in a clinical setting
Bibliographic record
Abstract
ABSTRACT Severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) continues to spread and evolve, giving rise to new surges in cases and deaths. Although nasopharyngeal swab (NPS) samples are the gold standard for diagnosing SARS-CoV2, NPS sampling is invasive and requires skilled staff, specialized transport medium, and nucleic acid extraction. The SalivaDirect method uses saliva samples and a simplified, flexible approach to overcome these drawbacks. In our study conducted at the COVID-19 Screening Unit of the Dhaka Hospital of icddr,b (International Centre for Diarrheal Disease Research, Bangladesh), the diagnostic performance of SalivaDirect and NPS was compared using paired samples. SARS-CoV2 was detected by performing RT-qPCR using RNA extracted from saliva samples with the SalivaDirect method and from the NPS with extracted RNA. A total of 200 participants were enrolled from February to March 2021, among whom 78 (39.0%) tested positive for SAR-CoV2 from at least one sample. Among the 78 participants testing positive, 65 (83.3%) tested positive in both specimens, eight (10.3%) tested positive only in NPS, and five (6.4%) tested positive only in saliva. SalivaDirect had a sensitivity of 89.0% and specificity of 96.1%, with NPS as the reference test. The sensitivity of NPS and SalivaDirect was 93.6% and 89.7% respectively, with a composite reference standard (where patients are defined as positive if tested positive in either method) as the reference. Our findings demonstrated that the SalivaDirect method can be used as an alternative to NPS in our clinical setting and also supports the use of SalivaDirect in other settings. IMPORTANCE Affordable and accessible tests for COVID-19 allow for timely disease treatment and pandemic management. SalivaDirect is a faster and easier method to implement than NPS sampling. Patients can self-collect saliva samples at home or in other non-clinical settings without the help of a healthcare professional. Sample processing in SalivaDirect is less complex and more adaptable than in conventional nucleic acid extraction methods. We found that SalivaDirect has good diagnostic performance and is ideal for large-scale testing in settings where supplies may be limited or trained healthcare professionals are unavailable.
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 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 | 0.001 | 0.001 |
| 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".