Diagnostic Accuracy of Assays Using Point-of-Care Testing or Dried Blood Spot Samples for the Determination of Hepatitis C Virus RNA: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Finger-stick point-of-care and dried blood spot (DBS) hepatitis C virus (HCV) RNA testing increases testing uptake and linkage to care. This systematic review evaluated the diagnostic accuracy of point-of-care testing and DBS to detect HCV RNA. METHODS: Bibliographic databases and conference presentations were searched for eligible studies. Meta-analysis was used to pool estimates. RESULTS: Of 359 articles identified, 43 studies were eligible and included. When comparing the Xpert HCV Viral Load Fingerstick assay to venous blood samples (7 studies with 987 samples), the sensitivity and specificity for HCV RNA detection was 99% (95% confidence interval [CI], 97%-99%) and 99% (95% CI, 94%-100%) and for HCV RNA quantification was 100% (95% CI, 93%-100%) and 100% (95% CI, 94%-100%). The proportion of invalid results following Xpert HCV Viral Load Fingerstick testing was 6% (95% CI, 3%-11%). When comparing DBS to venous blood samples (28 studies with 3988 samples) the sensitivity and specificity for HCV RNA detection was 97% (95% CI, 95%-98%) and 100% (95% CI, 98%-100%) and for HCV RNA quantification was 98% (95% CI, 96%-99%) and 100% (95% CI, 95%-100%). CONCLUSIONS: Excellent diagnostic accuracy was observed across assays for detection of HCV RNA from finger-stick and DBS samples. The proportion of invalid results following Xpert HCV Viral Load Fingerstick testing highlights the importance of operator training and quality assurance programs.
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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 | 0.002 | 0.148 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".