Intrahepatic Hepatitis C Viral Rna Status of Serum Polymerase Chain Reaction-Negative Individuals With Histological Changes on Liver Biopsy
Bibliographic record
Abstract
For individuals testing anti-HCV positive but negative for HCV RNA in serum, diagnosis remains unclear. Debate exists over whether these individuals have resolved infection or have similar clinical, histological, and virological profiles as serum PCR-positive individuals. The aim of this study was to assess the significance of histological changes in the liver of 33 serum PCR-negative women by investigation of clinical, histological, and intrahepatic HCV RNA status. For comparison, clinical and histological data from 100 serum PCR-positive women is presented. Viral RNA status was determined in snap-frozen liver biopsies using a sensitive nested PCR with an internal control. Although serum PCR-positive and -negative individuals shared similar age at diagnosis, source, and duration of infection, they differed from a clinical, histological, and virological perspective. Mean serum ALT levels were significantly lower in serum PCR-negative women (27.4 IU/L +/- 18 vs. 58.7 IU/L +/- 40 P <.001). Similarly, although inflammation (82%) and mild fibrosis (15%) were observed in PCR-negative biopsies, the mean HAI/fibrosis scores were significantly lower than in serum PCR-positive biopsies (1.9 +/- 1.5/0.15 +/- 0.4 vs. 4.2 +/- 1.4/1.1 +/- 1.3, respectively). Finally, HCV RNA was not detectable in serum PCR-negative liver biopsies but was detectable in all serum PCR-positive control biopsies. In conclusion, serum PCR-negative individuals may have mild histological abnormalities more suggestive of nonspecific reactive changes, steatosis or nonalcoholic steatohepatitis rather than chronic HCV, even when significant antibody responses are present in serum. Negative serum PCR status appears to reflect cleared past-exposure in liver.
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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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".