Multicenter Comparison of Roche COBAS AMPLICOR MONITOR Version 1.5, Organon Teknika NucliSens QT with Extractor, and Bayer Quantiplex Version 3.0 for Quantification of Human Immunodeficiency Virus Type 1 RNA in Plasma
Bibliographic record
Abstract
The performance and characteristics of Roche COBAS AMPLICOR HIV-1 MONITOR version 1.5 (CA MONITOR 1.5) UltraSensitive (usCA MONITOR 1. 5) and Standard (stCA MONITOR 1.5) procedures, Organon Teknika NucliSens HIV-1 RNA QT with Extractor (NucliSens), and Bayer Quantiplex HIV RNA version 3.0 (bDNA 3.0) were compared in a multicenter trial. Samples used in this study included 460 plasma specimens from human immunodeficiency virus (HIV) type 1 (HIV-1)-infected persons, 100 plasma specimens from HIV antibody (anti-HIV)-negative persons, and culture supernatants of HIV-1 subtype A to E isolates diluted in anti-HIV-negative plasma. Overall, bDNA 3.0 showed the least variation in RNA measures upon repeat testing. For the Roche assays, usCA MONITOR 1.5 displayed less variation in RNA measures than stCA MONITOR 1.5. NucliSens, at an input volume of 2 ml, showed the best sensitivity. Deming regression analysis indicated that the results of all three assays were significantly correlated (P < 0.0001). However, the mean difference in values between CA MONITOR 1.5 and bDNA 3.0 (0.274 log(10) RNA copies/ml; 95% confidence interval, 0.192 to 0.356) was significantly different from 0, indicating that CA MONITOR 1.5 values were regularly higher than bDNA 3.0 values. Upon testing of 100 anti-HIV-negative plasma specimens, usCA MONITOR 1.5 and NucliSens displayed 100% specificity, while bDNA 3.0 showed 98% specificity. NucliSens quantified 2 of 10 non-subtype B viral isolates at 1 log(10) lower than both CA MONITOR 1.5 and bDNA 3.0. For NucliSens, testing of specimens with greater than 1,000 RNA copies/ml at input volumes of 0.1, 0.2, and 2.0 ml did not affect the quality of results. Additional factors differing between assays included specimen throughput and volume requirements, limit of detection, ease of execution, instrument work space, and costs of disposal. These characteristics, along with assay performance, should be considered when one is selecting a viral load assay.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".