Subsidized optimal ART for HIV‐positive temporary residents of Australia improves virological outcomes: results from the Australian HIV Observational Database Temporary Residents Access Study
Bibliographic record
Abstract
INTRODUCTION: HIV-positive (HIV+) temporary residents living in Australia legally are unable to access government subsidized antiretroviral treatment (ART) which is provided via Medicare to Australian citizens and permanent residents. Currently, there is no information systematically being collected on non-Medicare eligible HIV+ patients in Australia. The objectives of this study are to describe the population recruited to the Australian HIV Observational Database (AHOD) Temporary Residents Access Study (ATRAS) and to determine the short- and long-term outcomes of receiving (subsidized) optimal ART and the impact on onwards HIV transmission. METHODS: ATRAS was established in 2011. Eligible patients were recruited via the AHOD network. Key HIV-related characteristics were recorded at baseline and prospectively. Additional visa-related information was also recorded at baseline, and updated annually. Descriptive statistics were used to describe the ATRAS cohort in terms of visa status by key demographic characteristics, including sex, region of birth, and HIV disease status. CD4 cell count (mean and SD) and the proportion with undetectable (<50 copies/ml) HIV viral load are reported at baseline, 6 and 12 months of follow-up. We also estimate the proportion reduction of onward HIV transmission based on the reduction in proportion of people with detectable HIV viral load. RESULTS: A total of 180 patients were recruited to ATRAS by June 2012, and by July 2013 39 patients no longer required ART via ATRAS, 35 of whom became eligible for Medicare-funded medication. At enrolment, 63% of ATRAS patients were receiving ART from alternative sources, 47% had an undetectable HIV viral load (<50 copies/ml) and the median CD4 cell count was 343 cells/µl (IQR: 222-479). At 12 months of follow-up, 85% had an undetectable viral load. We estimated a 75% reduction in the risk of onward HIV transmission with the improved rate of undetectable viral load. CONCLUSIONS: The immunological and virological improvements highlight the importance of supplying optimal ART to this vulnerable population. The increase in proportion with undetectable HIV viral load shows the potentially significant impact on HIV transmission in addition to the personal health benefit for each individual.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".