Injection Drug Use and Hepatitis C as Risk Factors for Mortality in HIV-Infected Individuals
Bibliographic record
Abstract
BACKGROUND: HIV-infected individuals with a history of transmission through injection drug use (IDU) have poorer survival than other risk groups. The extent to which higher rates of hepatitis C (HCV) infection in IDU explain survival differences is unclear. METHODS: Adults who started antiretroviral therapy between 2000 and 2009 in 16 European and North American cohorts with >70% complete data on HCV status were followed for 3 years. We estimated unadjusted and adjusted (for age, sex, baseline CD4 count and HIV-1 RNA, AIDS diagnosis before antiretroviral therapy, and stratified by cohort) mortality hazard ratios for IDU (versus non-IDU) and for HCV-infected (versus HCV uninfected). RESULTS: Of 32,703 patients, 3374 (10%) were IDU; 4630 (14%) were HCV+; 1116 (3.4%) died. Mortality was higher in IDU compared with non-IDU [adjusted HR 2.71; 95% confidence interval (CI): 2.32 to 3.16] and in HCV+ compared with HCV- (adjusted HR 2.65; 95% CI: 2.31 to 3.04). The effect of IDU was substantially attenuated (adjusted HR 1.57; 95% CI: 1.27 to 1.94) after adjustment for HCV, while attenuation of the effect of HCV was less substantial (adjusted HR 2.04; 95% CI: 1.68 to 2.47) after adjustment for IDU. Both IDU and HCV were strongly associated with liver-related mortality (adjusted HR 10.89; 95% CI: 6.47 to 18.3 for IDU and adjusted HR 14.0; 95% CI: 8.05 to 24.5 for HCV) with greater attenuation of the effect of IDU (adjusted HR 2.43; 95% CI: 1.24 to 4.78) than for HCV (adjusted HR 7.97; 95% CI: 3.83 to 16.6). Rates of CNS, respiratory and violent deaths remained elevated in IDU after adjustment for HCV. CONCLUSIONS: A substantial proportion of the excess mortality in HIV-infected IDU is explained by HCV coinfection. These findings underscore the potential impact on mortality of new treatments for HCV in HIV-infected people.
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How this classification was reachedexpand
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 | 0.003 | 0.011 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".