Hepatitis E virus as a transfusion transmitted infection-current status
Bibliographic record
Abstract
Objectives: Hepatitis E virus (HEV) infection is growing worldwide and presents a new threat to the blood transfusion services across the world. The present review tries to explore how the transfusion medicine community is responding to the threat. Materials and Methods: The major papers and important case reports were culled from PubMed, Science Direct, Embase related to this infection, and transfusion medicine since 2005 were explored and relevant articles were discussed with emphasis on epidemiology, infection, prevalence in donor population, susceptible recipients, prevention, and future development. Results: There are eight genotypes of this virus with different host, transmission biology, and clinical infection. Chronic infections are more common with Genotype 3 and Genotype 4 which are prevalent in Europe and transmitted by pig and meats cooked from this animal. Genotype 5 and 6 has not yet been linked to human transmission. Genotype 1 and Genotype 2 cause epidemic form of this infection and are common in developing countries. Immunosuppressed and chronic liver disease patients get chronic or severe infection. Pregnant ladies develop fulminant hepatitis with high mortality. The virus is transmitted by blood products but severe infection is uncommon. Many European countries, USA, Canada are using Nucleic Acid Testing (NAT) based technology to screen their donors as Individual Donor-NAT or Minipool NAT with varying efficiency. Large part of the world as yet has not taken any active measure to contain this infection through transfusion. A vaccine is available, effective but is not widely used as more studies are needed. Cross immunity does happen between genotypes and presence of immunoglobulin G antibody in blood protects against serious infection. Alanine transaminase level corresponds with viremia in asymptomatic but infected individuals. Conclusion: The HEV is an emerging but important threat to transfusion medicine service. Important information regarding this infection is still lacking. However, there is a need to develop robust safety algorithm to counter this threat and make transfusion safer.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".