Evaluation of a Public Health Referral System to Re-Engage Individuals Living With HIV Who Have Interrupted Antiretroviral Therapy in British Columbia, Canada
Bibliographic record
Abstract
BACKGROUND: In 2016, the British Columbia HIV/AIDS Drug Treatment Program modified its prescriber alert system for antiretroviral therapy (ART) interruptions to include referrals to regional public health nursing teams for direct outreach support for those who remain off treatment for 4 months or longer. We evaluated clinically relevant outcomes of this Re-Engagement and Engagement in Treatment for Antiretroviral Interrupted and Naïve populations (RETAIN) initiative, in comparison to previous time-periods. METHODS: We analyzed ART interruptions triggering alerts in pre-RETAIN (July 2013-April 2016) and post-RETAIN periods (May 2016-October 2017) with follow-up continuing until October 2018. We compared the proportions of those who restarted ART and achieved viral suppression in pre-RETAIN and post-RETAIN periods and the time to ART restart using generalized estimating equations. Cox proportional hazards modelling was used to examine associations with time-to-ART-restart. RESULTS: A total of 1805 individuals experienced ART interruptions triggering 3219 alerts; 2050 in pre-RETAIN and 1169 in post-RETAIN periods. Participants were predominantly men (74%) and had a median duration of ART of 5 years. Among persons who remained interrupted >4 months after an ART interruption alert was sent, the median time from interruption to ART re-initiation declined from 8.7 months to 7.4 months (P < 0.001) from pre-to post-RETAIN periods. Interruptions in the post-RETAIN era were associated with an increased hazard of restarting ART (adjusted hazard ratio 1.51; 95% CI: 1.34 to 1.69). CONCLUSIONS: Public health referrals shortened the length of ART interruptions after alerts sent to prescribers had not resulted in re-engagement. Similar programs should be considered in other jurisdictions.
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".