Analytical Performances of Human Immunodeficiency Virus Type 1 RNA-Based Amplix® Real-Time PCR Platform for HIV-1 RNA Quantification
Bibliographic record
Abstract
Objectives. We evaluated the performances of Amplix real-time PCR platform developed by Biosynex (Strasbourg, France), combining automated station extraction (Amplix station 16 Dx) and real-time PCR (Amplix NG), for quantifying plasma HIV-1 RNA by lyophilized HIV-1 RNA-based Amplix reagents targeting gag and LTR, using samples from HIV-1-infected adults from Central African Republic. Results. Amplix real-time PCR assay showed low limit of detection (28 copies/mL), across wide dynamic range (1.4–10 log copies/mL), 100% sensitivity and 99% specificity, high reproducibility, and accuracy with mean bias < 5%. The assay showed excellent correlations and concordance of 95.3% with the reference HIV-1 RNA load assay (Roche), with mean absolute bias of +0.097 log copies/mL by Bland-Altman analysis. The assay was able to detect and quantify the most prevalent HIV-1 subtype strains and the majority of non-B subtypes, CRFs of HIV-1 group M, and HIV-1 groups N and O circulating in Central Africa. The Amplix assay showed 100% sensitivity and 99.6% specificity to diagnose virological failure in clinical samples from antiretroviral drug-experienced patients. Conclusions. The HIV-1 RNA-based Amplix real-time PCR platform constitutes sensitive and reliable system for clinical monitoring of HIV-1 RNA load in HIV-1-infected children and adults, particularly adapted to intermediate laboratory facilities in sub-Saharan Africa.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".