Dynamics of HIV viremia and antibody seroconversion in plasma donors
Bibliographic record
Abstract
OBJECTIVES: The characterization of primary HIV infection by the analysis of serial plasma samples from newly infected persons using multiple standard viral assays. DESIGN: A retrospective study involving two sets of archived samples from HIV-infected plasma donors. (A) 435 samples from 51 donors detected by anti-HIV enzyme immunoassays donated during 1984-1994; (B) 145 specimens from 44 donors detected by p24 antigen screening donated during 1996-1998. SETTING: Two US plasma products companies. MAIN OUTCOME MEASURES: The timepoints of appearance of HIV-1 markers and viral load concentrations during primary HIV infection. RESULTS: The pattern of sequential emergence of viral markers in the 'A' panels was highly consistent, allowing the definition and estimation of the duration of six sequential stages. From the 'B' panels, the viral load at p24 antigen seroconversion was estimated by regression analysis at 10 000 copies/ml (95% CI 2000-93 000) and the HIV replication rate at 0.35 log copies/ml/day, corresponding to a doubling time in the preseroconversion phase of 20.5 h (95% CI 18.2-23.4 h). Consequently, an RNA test with 50 copies/ml sensitivity would detect HIV infection approximately 7 days before a p24 antigen test, and 12 days before a sensitive anti-HIV test. CONCLUSION: The sequential emergence of assay reactivity allows the classification of primary HIV-1 infection into distinct laboratory stages, which may facilitate the diagnosis of recent infection and stratification of patients enrolled in clinical trials. Quantitative analysis of preseroconversion replication rates of HIV is useful for projecting the yield and predictive value of assays targeting primary HIV infection.
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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 | 0.004 |
| 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 | 0.001 | 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".