Contribution of alcohol use disorders on the burden of chronic hepatitis C in France, 2008–2013: A nationwide retrospective cohort study
Bibliographic record
Abstract
BACKGROUND & AIMS: Hepatitis C virus (HCV) patients are at risk of alcohol use disorders (AUDs). We measured the contribution of AUDs on the burden of chronic HCV infection in French HCV patients. METHODS: The hospital trajectory of 97,347 French HCV patients aged 18-65 in January 2008 were tracked and followed until in-hospital death or December 2013. Primary outcome was the frequency of liver-related complications. Secondary outcomes were the frequency of liver transplantation and otherwise cause-specific mortality. Adjusted odds ratios (OR), population attributable risks of AUDs and other cofactors of liver disease progression associated with HCV transmission were measured. RESULTS: The 28,101 (28.9%) individuals with AUDs had the highest odds for liver-related complications (OR=7.19; 95% confidence interval [CI], 6.90 to 7.50), liver transplantation (OR=4.28; 95% CI, 3.80 to 4.82), and liver death (OR=6.20; 95% CI, 5.85 to 6.58). Alcohol rehabilitation and abstinence were associated with 60% (95% CI, 57% to 63%) and 78% (95% CI, 76% to 80%) reduction of liver-related complications, respectively. The attributable risk of AUDs was 71.8% (95% CI, 66.0 to 76.8) of 17,669 liver-related complications, 67.4% (95% CI, 61.6 to 72.4) of 1,599 liver transplantations, and 68.8% (95% CI, 63.4 to 73.5) of 6,677 liver deaths. The number of liver transplantations remained stable and the number of liver deaths increased, at a faster rate for individuals with AUDs, over the observational period. CONCLUSION: In France, AUDs contributed to more than two-thirds of the burden of chronic HCV infection in young and middle-aged adults over 2008-2013. LAY SUMMARY: This study tracked liver-related complications and mortality of all 97,347 young and middle-aged patients (18-65years old) discharged with chronic HCV infection from French hospitals over 2008-2013. About 30% patients were recorded with alcohol use disorders (AUDs) and had the highest odds for liver-related complications (i.e. decompensated cirrhosis and liver cancer). AUDs contributed to more than two-thirds of 1,599 liver transplantations and 6,677 liver deaths recorded in patients with chronic HCV infection over 2008-2013 in France. Alcohol rehabilitation and abstinence were associated with above a 50% risk reduction of liver-related complications. Promoting alcohol abstinence should receive high priority to reduce the burden of chronic HCV infection.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".