Sociodemographic risk factors for hepatitis C virus infection in a prospective cohort study of 257 persons in Canada who inject drugs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Approximately 60% of incident hepatitis C virus (HCV) infections are due to intravenous drug use; therefore, understanding the socio-demographics of people who inject drugs (PWID) is necessary to achieve HCV elimination. METHODS: In this prospective cohort study of PWID, we determined patients’ baseline HCV antibody, hepatitis B virus (HBV), and HIV serological status. HCV antibody– negative (anti-HCV-negative) cases were followed for seroconversion (median 17 mo with q3m testing) as part of a larger study to develop a vaccine for HCV. An interviewer-administered baseline questionnaire completed with all patients evaluated socio-demographic and clinical characteristics. RESULTS: We tested 257 PWID (median age 40 [range 49–31]y, 81% men, 63% Caucasian, 28% Indigenous). Of these, 28% were positive for HCV antibodies (anti-HCV-positive) (median age 42 [range 49–36]y, 74% men, 69% Caucasian, 29% Indigenous). Compared with anti-HCV-negative PWID, anti-HCV-positive PWID reported injecting more morphine and hydromorphone, using more hydromorphone via non-injection routes, and were more likely to be enrolled in methadone programs. More than 60% reported previous HCV testing, but recent testing (<2 y) was more frequent in the anti-HCV-negative group ( p = 0.03). All were HBV negative, but more than 50% of the anti-HCV-positive group had anti-HBs titres more than 10 IU/L compared with 35% of the anti-HCV-negative group ( p = 0.01), and 3 of 257 were HIV positive (1 co-infected with HCV–HIV). CONCLUSIONS: In this prospective study, differences in age, timing of HCV testing and risk behaviours were found between anti-HCV-positive and anti-HCV-negative groups.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it