Qualitative Detection of Hepatitis C Virus RNA: Comparison of Analytical Sensitivity, Clinical Performance, and Workflow of the Cobas Amplicor HCV Test Version 2.0 and the HCV RNA Transcription-Mediated Amplification Qualitative Assay
Bibliographic record
Abstract
The qualitative Cobas Amplicor hepatitis C virus (HCV) version 2.0 assay (HCV PCR) and the Bayer Reference Testing Laboratory HCV RNA transcription-mediated amplification assay (HCV TMA) were compared for analytical sensitivity, clinical performance, and workflow. Limits of detection were determined by testing dilutions of the World Health Organization HCV standard in replicates of 15 at concentrations of from 1.0 to 70 IU/ml. The limit of detection of the HCV PCR assay was calculated to be 45 IU/ml on initial testing and 32 IU/ml after resolution of gray zone results. The calculated limit of detection for HCV TMA was 6 IU/ml. To compare clinical performance, 300 specimens, grouped as follows, were evaluated: 112 samples that were indeterminate in an anti-HCV enzyme immunoassay (EIA) and for which HCV RNA was not detected by HCV PCR; 79 samples that were EIA positive and for which HCV RNA was not detected by HCV PCR; and 105 samples that were both EIA and HCV PCR positive. For these groups, interassay concordance ranged from 96.2% to 100%. In addition, three HCV PCR gray zone specimens and one neonatal specimen were also evaluated. A 64-sample run (full run, 91 specimens) required 5 h for testing by HCV TMA, whereas almost 8 h were required to test a full run of 22 specimens by HCV PCR. HCV TMA demonstrated excellent concordance with HCV PCR when clinical samples were tested. However, HCV TMA was more sensitive than HCV PCR, required less time for test result completion, and had a greater throughput.
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 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 | 0.024 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".