Performance of the Xpert HIV-1 Viral Load Assay: a Systematic Review and Meta-analysis
Bibliographic record
Abstract
ABSTRACT Viral load (VL) is the preferred treatment-monitoring approach for HIV-positive patients. However, more rapid, near-patient, and low-complexity assays are needed to scale up VL testing. The Xpert HIV-1 VL assay (Cepheid, Sunnyvale, CA) is a new, automated molecular test, and it can leverage the GeneXpert systems that are being used widely for tuberculosis diagnosis. We systematically reviewed the evidence on the performance of this new tool in comparison to established reference standards. A total of 12 articles (13 studies) in which HIV patient VLs were compared between Xpert HIV VL assay and a reference standard VL assay were identified. Study quality was generally high, but substantial variability was observed in the number and type of agreement measures reported. Correlation coefficients between Xpert and reference assays were high, with a pooled Pearson correlation ( n = 8) of 0.94 (95% confidence interval [CI], 0.89, 0.97) and Spearman correlation ( n = 3) of 0.96 (95% CI, 0.86, 0.99). Bland-Altman metrics ( n = 11) all were within 0.35 log copies/ml of perfect agreement. Overall, Xpert HIV-1 VL performed well compared to current reference tests. The minimal training and infrastructure requirements for the Xpert HIV-1 VL assay make it attractive for use in resource-constrained settings, where point-of-care VL testing is most needed.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.017 | 0.008 |
| 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 | 0.001 |
| 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".