P172 Emergency department opt-out testing for hepatitis C: a different risk profile and increased case-finding
Bibliographic record
Abstract
Opt-out testing for blood-borne viruses (BBV) in emergency departments (ED) is being rolled out nationally, following a London-based pilot. This is partly funded by the NHS hepatitis C elimination program to accelerate progress towards the WHO hepatitis C elimination target of 2030. This study assesses patient characteristics and engagement in care compared to standard referral pathways across a large representative cohort. We undertook a multicentre retrospective study of HCV RNA+ patients across 7 EDs from North and South London. Recruitment was between April 2022 and April 2024 for a minimum of 12 months with a 6-month follow-up period. Patient and disease characteristics were compared with those referred by standard routes in same period (community drug services, prisons, primary and secondary care – ‘non-ED’). A total of 342616 HCV Ab tests were performed at the study sites representing 28% of all tests performed in the programme this period. 253 HCV RNA+ patients were identified after exclusion of 18 false-positives. 28 patients were not contactable by phone or post. Of the remaining 225, 19 were already under follow-up and 206 were not under care. Of these, 174 were new to service and 32 were lost to follow-up. 183/206 (88.8%) were successfully engaged for clinical assessment. Of those assessed, a similar proportion progressed to treatment (90.7% ED versus 90.9% non-ED, 2-sided Pearson Chi Sq test, NS) and achieved sustained virological response (SVR12) within the censor dates (72.1% ED versus 73.5% non-ED, 2-sided Pearson Chi Sq test, NS). In the ED cohort, 30.4%, 18% and 9.9% of patients had liver stiffness measurements greater than 8.9, 11.4 and 19.9 kPa respectively. 3 new cases of HCC were identified. The ED cohort was significantly older (mean age 56.8 vs 50.1, p <0.001, 2-sided t-test) and the minority spoke English as a first language, whereas the inverse was true in the non-ED group (35.9% ED vs 69.5% in non-ED, 2-sided Pearson Chi Sq test, p<0.001). A history of past/current injected drug use was significantly lower in the ED cohort (26.5% ED vs 52.1% non-ED, P<0.001). HCV genotype distribution also differed significantly (genotype 1: 42% ED versus 69% non-ED, p < 0.001). ED testing resulted in a 40% increase in HCV assessments in the study period. ED opt-out HCV testing enhances case-finding in a population with different demographics and transmission risks than standard pathways and, with high rates of assessment and treatment, contributes meaningfully to HCV elimination efforts.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".