Reduced injection risk behavior with co-located hepatitis C treatment at a syringe service program: The accessible care model
Bibliographic record
Abstract
BACKGROUND: The main mode of transmission of Hepatitis C in North America is through injection drug use. Availability of accessible care for people who inject drugs is crucial for achieving hepatitis C elimination. OBJECTIVE: The objective of this analysis is to compare the changes in injection drug use frequency and high-risk injection behaviors in participants who were randomized to accessible hepatitis c care versus usual hepatitis c care. METHODS: Participants who were hepatitis C virus RNA positive and had injected drugs in the last 90 days were enrolled and randomized 1:1 to an on-site, low threshold accessible care arm or a standard, referral-based usual care arm. Participants attended follow-up appointments at 3, 6, 9, and 12 months during which they answered questions regarding injection drug use frequency, behaviors, and treatment for opioid use disorder. PRIMARY OUTCOMES: The primary outcomes of this secondary analysis are the changes in the frequency of injection drug use, high-risk injection behaviors, and receiving medication for opioid use disorder in the last 30 days. RESULTS: A total of 165 participants were enrolled in the study, with 82 participants in the accessible care arm and 83 participants in the usual care arm. Participants in the accessible care arm were found to have a statistically significant higher likelihood of reporting a lower range of injection days (accessible care-by-time effect OR = 0.78, 95% CI = 0.62-0.98) and injection events (accessible care-by-time effect OR = 0.70, 95% CI = 0.56-0.88) in the last 30 days at a follow-up interview relative to those in the usual care arm. There were no statistically significant differences in the rates of decrease in receptive sharing of injection equipment or in the percentage of participants receiving treatment for opioid use disorders in the two arms. CONCLUSION: Hepatitis C treatment through an accessible care model resulted in statistically higher rates of decrease in injection drug use frequency in people who inject drugs.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".