Impact of hepatitis C virus infection on all-cause and liver-related mortality in a large community-based cohort of inner city residents
Bibliographic record
Abstract
The aim of this study was to measure the impact of hepatitis C virus (HCV) infection on mortality in a cohort of inner city residents. The Community Health and Safety Evaluation is a community-based study of inner city residents followed retrospectively and prospectively through linkages with provincial virology and mortality databases. We identified participants having received HCV antibody testing, evaluated cause-specific mortality rates and factors associated with all-cause and liver-related mortality using Cox Proportional Hazards models. Overall, 2332 participants received HCV antibody testing (recent non-injection drug use - 81%). The prevalence of HCV and HIV was 64% (1495 of 2332) and 21% (485 of 2332), respectively. Between January 2003 and December 2007, there were 180 deaths (192 per 10.000 person-years; 95% CI: 165, 222), with 21% HIV-related, 20% drug-related and 7% liver-related. Mortality was associated with age >50 [adjusted hazard ratio (AHR) 2.80 vs < 40 years (referent group); 95% CI 1.93, 4.07, P < 0.001] and HIV infection (AHR 3.81; 95% CI 2.72, 5.34, P < 0.001), but not positive HCV antibody status (AHR 1.19; 95% CI 0.83, 1.72, P = 0.35). Liver-related mortality was associated with age >50 [AHR 18.49 vs < 40 years (referent group); 95% CI 2.27, 150.41, P < 0.001] and positive HCV antibody status (AHR 7.69; 95% CI 0.99, 59.98, P = 0.052). This study demonstrates a high rate of mortality in this population, particularly those with HIV. HCV-infected inner city residents >50 years of age were at significant risk of liver-related mortality. Continued surveillance of this population infected with HCV in the 1970s and 1980s is important.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".