Early Read‐Time Performance of the <scp>OraQuick HCV</scp> Rapid Antibody Assay for the Exclusion of <scp>HCV</scp> Viremia
Bibliographic record
Abstract
Rapid point-of-care tests for hepatitis C virus (HCV) provide results in 20 min and allow linkage to care, particularly for difficult-to-reach populations. Prior work suggested an early reading time of the OraQuick (OQ) rapid HCV antibody lateral flow immunoassay identified people with HCV viremia; however, these observations were not externally validated. We conducted a prospective cohort study at Penn Presbyterian Medical Center from June 2021 to August 2023 to evaluate the performance of OQ early reading times for HCV viremia among participants with reactive HCV antibody. Following test device insertion for whole blood substrate, the OQ assay was evaluated every minute from 5 to 10 min, then at 20 and 40 min. Early read time performance was evaluated against the standard of care HCV RNA. 175 participants (120 [68.6%] with detectable HCV viremia) completed the OQ assay. Among HCV viremic participants, 119 had a positive whole blood OQ by 7 min (sensitivity: 99.2% [95% confidence interval, CI: 95.4-100]; positive predictive value: 82.1% [95% CI: 74.8-87.9]); 1 viremic participant with severe immunosuppression was not identified at this early reading time. No time interval accurately identified only those with HCV viremia, yet a negative OQ test at 7 min excluded HCV viremia (negative predictive value: 96.3% [95% CI: 81.0-99.9]). A 7-min reading time for a whole blood OQ assay may reduce the need for HCV RNA testing and improve screening efficiency by identifying people without HCV viremia. Early read time results cannot be used to exclusively identify HCV viremia and should be used with caution in those with severe immunosuppression or if acute HCV infection is suspected.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".