Probability of a false-negative HIV antibody test result during the window period: a tool for pre- and post-test counselling
Bibliographic record
Abstract
Failure to understand the risk of false-negative HIV test results during the window period results in anxiety. Patients typically want accurate test results as soon as possible while clinicians prefer to wait until the probability of a false-negative is virtually nil. This review summarizes the median window periods for third-generation antibody and fourth-generation HIV tests and provides the probability of a false-negative result for various days post-exposure. Data were extracted from published seroconversion panels. A 10-day eclipse period was used to estimate days from infection to first detection of HIV RNA. Median (interquartile range) days to seroconversion were calculated and probabilities of a false-negative result at various time periods post-exposure are reported. The median (interquartile range) window period for third-generation tests was 22 days (19-25) and 18 days (16-24) for fourth-generation tests. The probability of a false-negative result is 0.01 at 80 days' post-exposure for third-generation tests and at 42 days for fourth-generation tests. The table of probabilities of falsely-negative HIV test results may be useful during pre- and post-test HIV counselling to inform co-decision making regarding the ideal time to test for HIV.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".