A review of Human Immunodeficiency Virus (HIV) rapid testing
Bibliographic record
Abstract
BACKGROUND: In Canada, it is estimated that 71,300 persons were living with HIV at the end of 2011. Approximately 25% (14,500 to 21,500) of prevalent cases were unaware of their HIV infection. Expanded use of HIV rapid tests may increase the detection of undiagnosed infections, enable earlier treatment and support services and prevent the onward transmission of HIV. OBJECTIVE: To examine patient acceptability, impact (defined as receipt of test results and linkage to care) and cost-effectiveness of HIV rapid tests. METHODS: (AMSTAR) tool was used to assess the included systematic reviews for methodological quality. Results were summarized narratively for each of the outcomes. RESULTS: Eight systematic reviews were included. Acceptability of HIV rapid tests was generally high in medical settings (69% to 98%) especially among pregnant women and youth attending emergency rooms but was lower in non-medical settings (14% to 46%). The percentage of people who obtained their test results was variable. It was high (83% to 93%) in emergency rooms but was low in a rapid care setting with regular business hours (27%). Impact on linkage to care was limited. Only one systematic review examined cost-effectiveness of rapid testing and concluded that HIV rapid tests were cost-effective in comparison to traditional methods; however, results were all based on static models. CONCLUSION: Overall, HIV rapid tests demonstrated generally high acceptability, variability in receiving test results and limited impact on linkage to care. While these findings suggest that HIV rapid tests may be useful, further research is needed to confirm in whom, when and where they are best used and how to ensure better linkage to care.
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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 | 0.010 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".