Viremia levels in hepatitis C infection among Egyptian blood donors and implications for transmission risk with different screening scenarios
Bibliographic record
Abstract
BACKGROUND: Knowledge about the viral load (VL) distributions in different stages of hepatitis C virus (HCV) infection is essential to compare the efficacy of serologic screening and nucleic acid testing (NAT) in preventing transfusion transmission risk. We studied HCV-RNA levels in Egyptian blood donors in the preseroconversion window period (WP) and in later anti-HCV-positive stages of infection. STUDY DESIGN AND METHODS: Subsets of individual-donation (ID)-NAT and anti-HCV-yield samples from a screening study among 119,756 donors were tested for VL by quantitative polymerase chain reaction (qPCR). Low viremia levels below the quantification limit of qPCR were determined by probit analysis using the proportion of reactive results on replicate NATs. Poisson distribution statistics were used to estimate transmission risk in different stages of HCV infection based on 50% minimum infectious doses (MID50 ) of 3.2 (1-10) and 316 (100-1000) virions in the absence and presence of anti-HCV, respectively. RESULTS: Rates of total HCV infections and WP-NAT-yield donations in two Egyptian blood centers varied between 2.6% to 4.5% and 1:3100 to 1:9500, respectively. VLs ranged from 82 to 3 × 10(7) copies/mL in WP and from fewer than 1600 to 1.6 × 10(6) copies/mL in anti-HCV-positive carrier donations. Only two (1.1%) of 175 donors with probable resolved infection had detectable RNA on replicate testing (estimated VLs of 0.5 and 1.8 copies/mL). This translates to an estimated transmission risk of 0.028% if ID-NAT-nonreactive, anti-HCV-positive donations would be used for RBC transfusions. CONCLUSION: Almost 99% of anti-HCV-reactive donations without detectable HCV-RNA on initial ID-NAT screening had eradicated the virus from the circulation, while 1% had extremely low VLs and are likely not infectious. The incremental safety offered by serologic testing of ID-NAT-screened blood seems minimal.
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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".