Hepatitis C virus transmission among oral crack users: viral detection on crack paraphernalia
Bibliographic record
Abstract
OBJECTIVE: Epidemiological studies present oral crack use as a potential independent risk factor for hepatitis C virus (HCV) status, yet actual HCV transmission pathways via crack use have not been evidenced. To this end, this exploratory study sought to detect HCV on crack-use paraphernalia used by street crack users. METHODS: Crack-use paraphernalia within 60 min of use was collected from 51 (N) street-crack users. HCV RNA detection was conducted through eluate sampling and manual RNA extraction. Participants provided a saliva sample to test for HCV antibody, and had a digital photograph taken of their oral cavities, to assess the presence of oral sores as a possible risk factor for oral HCV transmission. RESULTS: About 43.1% (n=22) of the study participants were HCV-antibody positive. One (2.0%) of the 51 pipes tested positive. A minority of the participants presented oral sores. The pipe on which HCV was detected was made from a glass stem; its owner was HCV-antibody positive, and there was full rater agreement on the presence of oral sores in the pipe owner's oral cavity. CONCLUSIONS: HCV transmission from an infected host onto paraphernalia as a precondition of HCV host-to-host transmission via shared crack paraphernalia use seems possible, with oral sores and paraphernalia condition constituting possible risk modifiers. Larger-scale studies with crack users are needed to corroborate our findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".