Rapid Whole-Blood Finger-Stick Test for HIV Antibody: Performance and Acceptability Among Women in Northern Thailand
Bibliographic record
Abstract
Although use of rapid HIV antibody tests of finger-stick blood specimens could expand voluntary counseling and testing in areas where fear of venipuncture and delays in learning test results are barriers, there is little information on performance and acceptability of these tests in Asia. We used the Hema. Strip HIV-1/2 test (Saliva Diagnostic Systems, Vancouver, WA) in a prospective cohort study of HIV seroincidence among women in northern Thailand from 1998 to 1999. Nurses obtained whole-blood specimens by finger-stick testing and provided test results and counseling at each visit. Acceptability of the rapid test was assessed at the first 6-month follow-up visit. HIV-1 seroprevalence among the 804 women screened at enrollment was 3.1%. Positive rapid test results from 25 women were confirmed by enzyme immunoassay and Western blot analysis using serum obtained by venipuncture. Of the 741 women who returned for follow-up, 56% preferred specimen collection by finger-stick testing to venipuncture, 80% preferred immediate rather than delayed test results, 79% preferred the rapid test method to typical testing methods, and 97% were satisfied with the test method used. Results from this study demonstrate the utility and acceptability of the rapid finger-stick test for HIV antibody among women in northern Thailand.
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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 | 0.000 | 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".