Options to Expand HIV Viral Load Testing in South Africa: Evaluation of the GeneXpert® HIV-1 Viral Load Assay
Bibliographic record
Abstract
BACKGROUND: Expansion of HIV viral load (VL) testing services are required to meet increased targets for monitoring patients on antiretroviral treatment. South Africa currently tests >4million VLs per annum in 16 highly centralised, automated high-throughput laboratories. The Xpert HIV-1 VL assay (Cepheid) was evaluated against in-country predicates, the Roche Cobas Taqmanv2 and Abbott HIV-1RT, to investigate options for expanding VL testing using GeneXpert's random access, polyvalent capabilities and already established footprint in South Africa with the Xpert MTB/RIF assay (207 sites). Additionally, the performance of Xpert HIV-1VL on alternative, off-label specimen types, Dried Blood Spots (DBS) and whole blood, was investigated. METHOD: Precision, accuracy (agreement) and clinical misclassification (1000cp/ml) of Xpert HIV-1VL plasma was compared to Taqmanv2 (n = 155) and Abbott HIV-1 RT (n = 145). Misclassification of Xpert HIV-1VL was further tested on DBS (n = 145) and whole blood (n = 147). RESULTS: Xpert HIV-1VL demonstrated 100% concordance with predicate platforms on a standardised frozen, plasma panel (n = 42) and low overall percentage similarity CV of 1.5% and 0.9% compared to Taqmanv2 and Abbott HIV-1 RT, respectively. On paired plasma clinical specimens, Xpert HIV-1VL had low bias (SD 0.32-0.37logcp/ml) and 3% misclassification at the 1000cp/ml threshold compared to Taqmanv2 (fresh) and Abbott HIV-1 RT (frozen), respectively. Xpert HIV-1VL on whole blood and DBS increased misclassification (upward) by up to 14% with increased invalid rate. All specimen testing was easy to perform and compatible with concurrent Xpert MTB/RIF Tuberculosis testing on the same instrument. CONCLUSION: The Xpert HIV-1VL on plasma can be used interchangeably with existing predicate platforms in South Africa. Whole blood and DBS testing requires further investigation, but polyvalency of the GeneXpert offers a solution to extending VL testing services.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".