Performance of <scp>HCV</scp> core antigen and <scp>PCR</scp> testing in a predominantly genotype 3 population
Bibliographic record
Abstract
Hepatitis C core antigen (HCVcAg) is becoming increasingly recognized as an alternative to molecular testing for the confirmation of chronic hepatitis C. However, there are limited data on the performance of this assay in a genotype 3 (GT3) predominant country like Pakistan. We conducted a study to evaluate the diagnostic performance of HCVcAg against the HCV polymerase chain reaction (PCR) molecular test. HCV antibody-positive patients requiring confirmatory testing were recruited from August to October 2018 at the Pakistan Kidney and Liver Institute and Research Center (PKLI&RC), Lahore, Pakistan. Patients with previously known diagnoses or treatment histories were excluded. The Abbott HCV Ag assay was used for HCVcAg testing. Results ≥3.00 fmol/L were considered positive for HCVcAg. The Abbott RealTime HCV assay was used for PCR testing with a lower detection limit of ≥12 IU/mL. We computed the sensitivity, specificity and correlation of HCVcAg against HCV PCR. A total of 394 patients were recruited. The median age of the patients was 42 years. Most participants were females (51.5%, n = 203), 30.7% (n = 121) had HTN, 10.4% DM (n = 41) and 5% had APRI ≥2. The overall sensitivity was 98.0% and the specificity was 98.6%. The lowest detection limit of cAg was an HCV RNA value of 4657 IU/mL. The levels of cAg were highly correlated with those of HCV RNA by Spearman's rank correlation test (r = 0.935, p < .001). HCVcAg represents a suitable alternative with high sensitivity and specificity compared with HCV PCR in the GT3-predominant population and can be incorporated into algorithms to improve linkage to care.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".