Long‐term morbidity and mortality in a Canadian post‐transfusion hepatitis C cohort: Over 15 years of follow‐up
Bibliographic record
Abstract
The Federal Government of Canada established a $1.1 billion compensation programme in 1999 to support individuals who acquired hepatitis C virus (HCV) through blood products between January 1986 and July 1990. We aimed to describe the morbidity and mortality of this unique post-transfusion cohort (n = 4550) followed for over 15 years from 2000 to 2016. The age-standardized mortality rates were compared with that of the Canadian general population and HCV cohorts from other countries. We evaluated all-cause mortality using Kaplan-Meier survival curves and HCV-related and unrelated mortality using competing risk models. The age-standardized all-cause and HCV-related mortality rates per 10 000 person-years were 127 (95% CI: 117-138) and 76 (95% CI: 69-85) for males, and 77 (95% CI: 69-87) and 43 (95% CI: 37-51) for females, respectively. The risk of death of the post-transfusion cohort was almost twice as high as the Canadian general population (rate ratio = 1.8; 95% CI: 1.7-1.9). All-cause, HCV-related and HCV-unrelated mortality were 20%, 12% and 8%, respectively at 15 years of follow-up. By comparison, HCV-related mortality rates per 10 000 person-years for population-based HCV cohorts varied from 18 and 11 in Australia to 65 and 43 in Scotland for males and females, respectively. We reported long-term follow-up data for the largest post-transfusion cohort in the literature. The all-cause mortality rates were markedly higher than that of the Canadian general population. We also showed that HCV-related mortality were greater compared to other HCV cohorts. This suggests that continued efforts to identify and treat post-transfusion HCV are warranted.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 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".