Seropositivity for Anti-HCV Core Antigen is Independently Associated With Increased All-Cause, Cardiovascular, and Liver Disease-Related Mortality in Hemodialysis Patients
Bibliographic record
Abstract
BACKGROUND: It is not known whether chronic or past hepatitis C virus (HCV) infection contributes to the high mortality rate in hemodialysis patients. METHODS: This prospective study of 1077 adult hemodialysis patients without hepatitis B virus infection used Poisson regression analysis to estimate crude and sex- and age-adjusted rates (per 1000 patient-years) of all-cause, cardiovascular, infectious disease-related and liver disease-related mortality in patients negative for HCV antibody (group A), patients positive for HCV antibody and negative for anti-HCV core antigen (group B), and patients positive for anti-HCV core antigen (group C). The relative risks (RRs) for each cause of death in group B vs group C as compared with those in group A were also estimated by Poisson regression analysis after multivariate adjustment. RESULTS: A total of 407 patients died during the 5-year observation period. The sex- and age-adjusted mortality rate was 71.9 in group A, 80.4 in group B, and 156 in group C. The RRs (95% CI) for death in group B vs group C were 1.23 (0.72 to 2.12) vs 1.60 (1.13 to 2.28) for all-cause death, 0.75 (0.28 to 2.02) vs 1.64 (0.98 to 2.73) for cardiovascular death, 1.64 (0.65 to 4.15) vs 1.58 (0.81 to 3.07) for infectious disease-related death, and 15.3 (1.26 to 186) vs 28.8 (3.75 to 221) for liver disease-related death, respectively. CONCLUSIONS: Anti-HCV core antigen seropositivity independently contributes to elevated risks of all-cause and cause-specific death. Chronic HCV infection, but not past HCV infection, is a risk for death among hemodialysis patients.
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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 | 0.003 |
| 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 | 0.001 |
| 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".