P312 Evaluation of an antiretroviral therapy (ART) interruption alert and referral system in british columbia (BC), canada
Bibliographic record
Abstract
Background In mid-2016, the BC HIV Drug Treatment Program (DTP) expanded its province-wide prescriber alert system for ART interruptions to include direct referrals to public health offices for persons off treatment for >4 months. We examined outcomes before and after launch of this Re-Engagement and Engagement in Treatment for Antiretroviral Interrupted and Naïve populations (RETAIN) Initiative. Methods We analyzed adult, DTP participants with ART interruptions triggering a physician-directed alert (ART refill >2 months late) in pre-RETAIN (Jul-2013 to Apr-2016) and post-RETAIN (May-2016 to Oct-2017) periods, based on the first alert issued within the study period. Follow-up continued until Oct-2018, excluding persons who moved or died within 90 days of an alert being sent. We compared the proportion of persons who were linked to care, re-started ART, or achieved viral suppression in the pre- and post-RETAIN periods, and the time to ART re-initiation using a generalized estimating equation model. Results There were 3219 alerts sent for 1805 patients, 1374 related to first interruptions in the pre-RETAIN period and 431 post-RETAIN. Of these, 135/431 (31%) post-RETAIN cases were referred to public health within 4 months following the first alert. Patients were predominantly male (74%) with a median age of 47 years. We found no statistically significant differences in the proportions of persons who were linked to care (83% vs 83%), re-started ART within 4 months (73% vs 74%), or achieved viral suppression (61% vs 62%) between the two periods. Among persons who re-initiated ART >4 months following the initial alert, the median (Q1-Q3) time to ART restart declined significantly from 9 (6–15) months pre-RETAIN to 8 (6–11) months post-RETAIN (p=0.004), possibly influenced by public health intervention. Conclusion We observed shorter time to re-initiation after the introduction of referrals for public health support. Similar systems could be considered in other jurisdictions. Disclosure No significant relationships.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".