Prevalence and Estimated Incidence of Blood-Borne Viral Pathogen Infection in Organ and Tissue Donors from Northern Alberta
Bibliographic record
Abstract
To determine the potential safety benefit of introducing nucleic acid testing (NAT) in tissue and organ donors, the risk of virus transmission was examined in a Canadian population. Anonymous data on Northern Alberta tissue and organ donors from 1998 to 2004 were used to determine the seroprevalence and estimate the seroincidence and residual risk of HIV, HBV, HCV and HTLV infection. Of the 3372 donors identified, 71.1% were surgical bone, 13.2% were living organ and 15.6% were deceased organ/tissue donors. Seroprevalence was: HIV 0.00%, HBV 0.09%, HCV 0.48% and HTLV 0.03%. Incidence (/100,000 p-yrs) and residual risks (/100,000 donors) could only be estimated for HBV (24.2 and 3.9) and HCV (11.2 and 2.2). Risk estimates were higher for deceased donors than surgical bone donors. HCV had the highest prevalence and HBV had the highest estimated incidence. HIV and HTLV risks were extremely low precluding accurate quantification. In this region of low overall viral prevalence, HCV NAT would be most effective in deceased organ donors. In surgical bone donors the cost of implementing NAT is high without significant added safety benefit.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".