Concurrent Hepatitis C and B Virus and Human Immunodeficiency Virus Infections Are Associated With Higher Mortality Risk Illustrating the Impact of Syndemics on Health Outcomes
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: Hepatitis C virus (HCV), hepatitis B virus (HBV), and human immunodeficiency virus (HIV) infections are associated with significant mortality globally and in North America. However, data on impact of concurrent multiple infections on mortality risk are limited. We evaluated the effect of HCV, HBV, and HIV infections and coinfections and associated factors on all-cause mortality in British Columbia (BC), Canada. METHODS: The BC Hepatitis Testers Cohort includes ~1.7 million individuals tested for HCV or HIV, or reported as a case of HCV, HIV, or HBV from 1990 to 2015, linked to administrative databases. We followed people with HCV, HBV, or HIV monoinfection, coinfections, and triple infections from their negative status to date of death or December 31, 2016. Extended Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for factors associated with all-cause mortality. RESULTS: Of 658 704 individuals tested for HCV, HBV, and HIV, there were 33 804 (5.13%) deaths. In multivariable Cox regression analysis, individuals with HCV/HBV/HIV (HR, 8.9; 95% CI, 8.2-9.7) infections had the highest risk of mortality followed by HCV/HIV (HR, 4.8; 95% CI, 4.4-5.1), HBV/HIV (HR, 4.1; 95% CI, 3.5-4.8), HCV/HBV (HR, 3.9; 95% CI, 3.7-4.2), HCV (HR, 2.6; 95% CI, 2.6-2.7), HBV (HR, 2.2; 95% CI, 2.0-2.3), and HIV (HR, 1.6; 95% CI, 1.5-1.7). Additional factors associated with mortality included injection drug use, problematic alcohol use, material deprivation, diabetes, chronic kidney disease, heart failure, and hypertension. CONCLUSIONS: Concurrent multiple infections are associated with high mortality risk. Substance use, comorbidities, and material disadvantage were significantly associated with mortality independent of coinfection. Preventive interventions, including harm reduction combined with coinfection treatments, can significantly reduce mortality.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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