HIV Point-of-Care Testing in Canadian Settings: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: HIV point-of-care testing (POCT) was approved for use in Canada in 2005 and provides important public health benefits by providing rapid screening results rather than sending a blood sample to a laboratory and waiting on test results. Access to test results soon after testing (or during the same visit) is believed to increase the likelihood that individuals will receive their results and improve access to confirmatory testing and linkages to care. This paper reviews the literature on the utilization of HIV POCT across Canadian provinces. METHODS: We searched OVID Medline, Embase, EBM Reviews, PsycINFO, CINAHL, and 20 electronic grey literature databases. All empirical studies investigating HIV POCT programs in Canada published in French or English were included. RESULTS: Searches of academic databases identified a total of 6,091 records. After removing duplicates and screening for eligibility, 27 records were included. Ten studies are peer-reviewed articles, and 17 are grey literature reports. HIV POCT in Canada is both feasible and accepted by Canadians. It is preferred to conventional HIV testing (ranging from 81.1 to 97%), and users are highly satisfied with the testing process (ranging between 96 and 100%). CONCLUSION: The majority of studies demonstrate that HIV POCT is feasible, preferred, and accepted by diverse populations in Canada. Losses to follow-up and linkage rates are also good. However, more research is needed to understand how best to scale up HIV POCT in contexts that currently have very limited or no access to testing.
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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 | 0.022 | 0.094 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.033 | 0.062 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".