Antiretroviral Therapy Reduces the Rate of Hepatic Decompensation Among HIV- and Hepatitis C Virus–Coinfected Veterans
Bibliographic record
Abstract
BACKGROUND: Human immunodeficiency virus (HIV) coinfection accelerates the rate of liver disease outcomes in individuals chronically infected with hepatitis C virus (HCV). It remains unclear to what degree combination antiretroviral therapy (ART) protects against HCV-associated liver failure. METHODS: We evaluated 10 090 HIV/HCV-coinfected males from the Veterans Aging Cohort Study Virtual Cohort, who had not initiated ART at entry, for incident hepatic decompensation between 1996 and 2010. We defined ART initiation as the first pharmacy fill date of a qualifying ART regimen of ≥3 drugs from ≥2 classes. Hepatic decompensation was defined as the first occurrence of 1 hospital discharge diagnosis or 2 outpatient diagnoses for ascites, spontaneous bacterial peritonitis, or esophageal variceal hemorrhage. To account for potential confounding by indication, marginal structural models were used to estimate hazard ratios (HRs) of hepatic decompensation, comparing initiation of ART to noninitiation. RESULTS: We observed 645 hepatic decompensation events in 46 444 person-years of follow-up (incidence rate, 1.4/100 person-years). Coinfected patients who initiated ART had a significantly reduced rate of hepatic decompensation relative to noninitiators (HR = 0.72; 95% confidence interval [CI], .54-.94). When we removed individuals with HIV RNA ≤400 copies/mL at baseline from the analysis (assuming that they may have received undocumented ART at entry), the hazard ratio became more pronounced (HR = 0.59; 95% CI, .43-.82). CONCLUSIONS: Initiation of ART significantly reduced the rate of hepatic decompensation by 28%-41% on average. These results suggest that ART should be administered to HIV/HCV-coinfected patients to lower the risk of end-stage liver disease.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".