High frequency of occult HCV infection in HD patients
Bibliographic record
Abstract
Occult HCV infection in liver and peripheral blood mononuclear cells (PBMC) of patients with cryptogenic chronic hepatitis (anti‐HCV, serum HCV RNA negative) and no renal diseases, has been reported (1). In this work we studied the existence of occult HCV infection in PBMC of HD patients. Inclusion criteria: high ALT (>28 IU/l) and/or gamma‐GPT levels, negative serological HCV and HBV markers (anti‐HCV, serum HCV‐RNA and HBsAg negative), and exclusion of other causes of liver damage. Four Spanish HD units participated in the study and 40 patients were enrolled; 40 (25 males) fulfilled the inclusion criteria. HCV‐RNA in PBMC was tested by RT‐PCR and by in situ hybridization. Occult HCV infection was found in 24/40 (60%) patients by RT‐PCR and all cases were confirmed by in situ hybridization. No differences were found regarding gender, etiology of renal disease, or fluctuant or persistent abnormal liver enzymes values. Among patients with occult HCV infection, 4/24 (16.7%) had only increased ALT levels; 7/24 (29.2.%) GGTP values; and both enzymes were elevated in 13/24 (54.2%). In our population, 60% HD patients with persistent or fluctuant ALT and/or GGTP values of unknown etiology and negative for serological viral markers (including serum HCV‐RNA) have an occult HCV infection in PBMC and these patients could be potentially infectious. (1)J Infect Dis 2004;189: 7–14.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".