Prospective study of hepatitis C virus infection in hemodialysis patients by monthly analysis of HCV RNA and antibodies
Bibliographic record
Abstract
The aims of this study were to (i) evaluate the prevalence and the incidence of hepatitis C virus (HCV) infection in hemodialysis patients in two different centers in São Paulo (Brazil), (ii) determine the time required to detect HCV infection among these patients by serology or PCR, (iii) establish the importance of alanine aminotransferase determination as a marker of HCV infection, and (iv) identify the HCV genotypes in this population. Serum samples were collected monthly for 1 year from 281 patients admitted to hospital for hemodialysis. Out of 281 patients, 41 patients (14.6%) were HCV positive; six patients seroconverted during this study (incidence = 3.1/1000 person-month). In 1.8% (5/281) of cases, RNA was detected before the appearance of antibodies (up to 5 months), and in 1.1% (3/281) of cases, RNA was the unique marker of HCV infection. The genotypes found were 1a, 1b, 3a, and 4a. The presence of genotype 4a is noteworthy, since it is a rare genotype in Brazil. These data pointed out the high prevalence and incidence of HCV infection at hemodialysis centers in Brazil and showed that routine PCR is fundamental for improving the detection of HCV carriers among patients undergoing hemodialysis.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".