Performance and Cost Evaluation of One Commercial andSix In-House Conventional and Real-Time ReverseTranscription-PCR Assays for Detection of Severe AcuteRespiratory SyndromeCoronavirus
Bibliographic record
Abstract
We evaluated seven reverse transcription-PCR (RT-PCR) assays, including six in-house assays and one commercial assay for the detection of severe acute respiratory syndrome coronavirus (SARS-CoV) RNA in clinical specimens. RT-PCR assays targeted different genomic regions and included three conventional assays (one nested and two non-nested) run on a conventional heat block and four real-time assays performed in a LightCycler (LC; Roche Diagnostics). All in-house assays were optimized for assay parameters, including MgCl2, primer, and probe concentrations. The commercial assay was the RealArt HPA CoV RT-PCR assay (Artus), which was run in the LC. Testing serial dilutions of cultured SARS-CoV showed that the analytical sensitivity of the assays ranged from 10(-8) to 10(-6), corresponding to 1 and 100 copies of viral RNA, respectively. Significant differences in analytical sensitivities were observed between assays (P < 0.01, probit regression analysis for 50% sensitivity levels for the top two assays versus the others). Testing 68 clinical specimens (including 17 respiratory tract specimens, 29 urine samples, and 22 stools or rectal swabs) demonstrated that six of the seven assays detected at least 17 of 18 positives (defined as positive in at least two assays), and two of the assays had a sensitivity of 100%. There were no significant differences in sensitivity between the assays (P = 0.5 [Cochrance Q test, least sensitive 15 of 18 versus 18 of 18]). The specificities of the assays ranged from 94.0 to 100% without significant differences (P = 0.25 to 0.5 [McNemar test]). The reagent and technologist cost of performing the in-house PCR assays ranged from $5.46 to $9.81 Canadian dollars (CDN) per test. The commercial assay cost was considerably higher at $40.37 per test. The results demonstrated good performance for all assays, providing laboratories that need to do SARS RNA testing with a choice of assay formats.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| 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".