Prevalence of Hepatitis (A–E) and HTLV‐I/II Infection Markers in Hemodialysis Patients of Central Greece
Bibliographic record
Abstract
Objective: The aim of this study was to assess the prevalence of serological and molecular markers of hepatitis (A–E) and human T‐lymphotropic viruses (HTLV) in hemodialysis (HD) patients of central Greece. Methods: 370 patients (246 males, 60 ± 14 years) attending the renal units (RUs) of central Greece (n = 5) were tested for anti‐HAV IgG, hepatitis B virus markers, anti‐HCV, anti‐HEV, and anti‐HTLV‐I/II with ELISA. In 131 casual samples, regardless of anti‐HCV status, a sensitive, qualitative HCV‐RNA assay (Versant ® , Bayer) based on transcription‐mediated amplification (TMA) was applied. Results: Previous HBV infection (anti‐HBc) was found in 48% and current HBV infection in 5.5% (HbsAg) of the patients. Anti‐HAV was detected in 94% while anti‐HDV and anti‐HTLV were negative. Anti‐HCV prevalence was 23% varying from 11 to 36% in the different RUs. Frequency of anti‐HEV (4.1%) was also highly varying (1.4–9.8%). There was no association between the infection markers and age, sex, or history of transfusion. Anti‐HCV correlated with duration of HD. HCV‐RNA was detected in 44/131 samples. In 15 cases results of anti‐HCV and TMA were contradicting. Two anti‐HCV negative samples were HCV‐RNA positive (2.3%). Conclusion: In RUs of central Greece, a high prevalence of HCV infection was found, associated with the duration of HD. The high prevalence of anti‐HEV found in 1 RU must be investigated further. In some of anti‐HCV‐negative patients viremia was detected. This result indicates that a considerable number of HCV infections are serologically occult. HCV‐RNA testing, regardless of the anti‐HCV status, has to be considered seriously in HD patients.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".