Detection of HIV-1 and HCV Infections among Antibody-Negative Blood Donors by Nucleic Acid–Amplification Testing
Bibliographic record
Abstract
BACKGROUND: Testing of blood donors for human immunodeficiency virus type 1 (HIV-1) and hepatitis C virus (HCV) RNA by means of nucleic acid amplification was introduced in the United States as an investigational screening test in mid-1999 to identify donations made during the window period before seroconversion. METHODS: We analyzed all antibody-nonreactive donations that were confirmed to be positive for HIV-1 and HCV RNA on nucleic acid-amplification testing of "minipools" (pools of 16 to 24 donations) by the main blood-collection programs in the United States during the first three years of nucleic acid screening. RESULTS: Among 37,164,054 units screened, 12 were confirmed to be positive for HIV-1 RNA--or 1 in 3.1 million donations--only 2 of which were detected by HIV-1 p24 antigen testing. For HCV, of 39,721,404 units screened, 170 were confirmed to be positive for HCV RNA, or 1 in 230,000 donations (or 1 in 270,000 on the basis of 139 donations confirmed to be positive for HCV RNA with the use of a more sensitive HCV-antibody test). The respective rates of positive HCV and HIV-1 nucleic acid-amplification tests were 3.3 and 4.1 times as high among first-time donors as among donors who gave blood repeatedly. Follow-up studies of 67 HCV RNA-positive donors demonstrated that seroconversion occurred a median of 35 days after the index donation, followed by a low rate of resolution of viremia; three cases of long-term immunologically silent HCV infection were documented. CONCLUSIONS: Minipool nucleic acid-amplification testing has helped prevent the transmission of approximately 5 HIV-1 infections and 56 HCV infections annually and has reduced the residual risk of transfusion-transmitted HIV-1 and HCV to approximately 1 in 2 million blood units.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".