Evidence for optimal HIV screening and testing intervals in HIV-negative individuals from various risk groups: A systematic review
Bibliographic record
Abstract
BACKGROUND: Human immunodeficiency virus (HIV) testing plays a crucial role in Canada's HIV prevention and treatment efforts and is the first step to achieving the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 targets; however, how often Canadians, including populations at increased risk of HIV exposure, should be tested is unclear. We conducted a systematic literature review to determine the optimal HIV screening and testing intervals. OBJECTIVE: To examine the current evidence on HIV testing intervals in HIV-negative individuals from various risk groups and to assess the potential harms and patients' values and preferences associated with different testing frequencies. METHODS: We searched MEDLINE/PubMed, Scopus, Embase, the Cochrane Library, PsychINFO and EconLit for studies on different frequencies of HIV testing published between January 2000 and September 2016. An additional search was conducted for grey literature published between January 2000 and October 2016. Data extraction included study characteristics, participants, exposure, outcomes and economic variables. The quality of the studies was assessed and results summarized. RESULTS: Of the 2,702 articles identified from the searches, 27 met the inclusion criteria for review. This included assessments of HIV testing intervals among the general population, men who have sex with men, people who use injection drugs and sex workers. Optimal testing intervals across risk groups ranged from one-time testing to every three months. Data from modelling studies may not be representative of the Canadian context. Few studies identified potential harms of increased screening, specifically an increase in both false positive and false negative results. There were only two studies that addressed patient values and preferences concerning HIV screening, which suggested that the majority of participants were amenable to routine screening through their primary care provider. CONCLUSION: There was insufficient evidence to support optimal HIV screening and testing intervals for different populations. Context-specific factors, such as budget allocation, human resources, local epidemiology, socioeconomic factors and risk behaviours, along with clinical judgement, inform whom and how often to screen, suggesting the need for research specific to Canada. Research on patient preferences as well as the benefits and harms of more frequent screening are also indicated.
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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 | 0.016 | 0.094 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".