An international review of the characteristics of viral nucleic acid‐amplification testing (NAT) reveals a trend towards the use of smaller pool sizes and individual donation NAT
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Nucleic acid-amplification testing (NAT) is used for screening blood donations/donors for blood-borne viruses. We reviewed global viral NAT characteristics and NAT-yield confirmatory testing used by blood operators. MATERIALS AND METHODS: NAT characteristics and NAT-yield confirmatory testing used during 2019 was surveyed internationally by the International Society of Blood Transfusion Working Party Transfusion-Transmitted Infectious Diseases. Reported characteristics are presented herein. RESULTS: NAT was mainly performed under government mandate. Human immunodeficiency virus (HIV), hepatitis C virus (HCV) and hepatitis B virus (HBV) NAT was performed on all donors and donation types, while selective testing was reported for West Nile virus, hepatitis E virus (HEV), and Zika virus. Individual donation NAT was used for HIV, HCV and HBV by ~50% of responders, while HEV was screened in mini-pools by 83% of responders performing HEV NAT. Confirmatory testing for NAT-yield samples was generally performed by NAT on a sample from the same donation or by NAT and serology on samples from the same donation and a follow-up sample. CONCLUSION: In the last decade, there has been a trend towards use of smaller pool sizes or individual donation NAT. We captured characteristics of NAT internationally in 2019 and provide insights into confirmatory testing approaches used for NAT-yields, potentially benefitting blood operators seeking to implement NAT.
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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 | 0.003 |
| 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 | 0.000 |
| 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".