Clinical Utility of HCV Core Antigen Detection and Quantification in the Diagnosis and Management of Patients with Chronic Hepatitis C Receiving an All-Oral, Interferon-Free Regimen
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The introduction of highly potent direct-acting combination therapies for HCV have negated the role of response-guided therapy and reduced the role of treatment monitoring. However, there remains a need to identify patients who are actively infected with HCV and discriminate those who have achieved sustained virological response (SVR) from those who fail to achieve SVR. METHODS: TaqMan HCV RNA 2.0 assay. RESULTS: Using 10 fmol/l as the clinical cutoff for cAg, the HCV RNA and cAg tests were in 100% agreement for true negative samples and 99.6% agreement for truly positive samples. One discordant (screening) sample was identified. This sample was target not detected by HCV RNA method but positive by anti-HCV and highly positive by ARCHITECT core antigen (7,912 fmol/l). Seventeen samples had cAg levels in the 'grey zone' >3 but <10 fmol/l at initial testing and were re-tested per package insert. All of these samples gave a result of <3 fmol/l upon retest. These results were in alignment with target not detected HCV RNA result. One sample had a cAg >3 but <10 fmol/l when tested on three consecutive occasions (5.8, 5.5 and 4.4) but had a target not detected RNA result. CONCLUSIONS: In this study cAg, with a 10 fmol/l cutoff, accurately identified 99.6% of patients with active viraemia and discriminated all subjects who achieved SVR from those who failed therapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it