Determinants of Liver Complications Among HIV/Hepatitis B Virus–Coinfected Patients
Bibliographic record
Abstract
BACKGROUND: Hepatitis B virus (HBV) infection is a leading cause of end-stage liver disease (ESLD) and hepatocellular carcinoma (HCC) in HIV. Factors contributing to the high rates of liver complications among HIV/HBV-coinfected individuals remain unknown. SETTING: North American AIDS Cohort Collaboration on Research and Design. METHODS: We performed a retrospective cohort study among HIV/HBV-coinfected patients in 10 US and Canadian cohorts of the North American AIDS Cohort Collaboration on Research and Design that validated ESLD (ascites, spontaneous bacterial peritonitis, variceal hemorrhage, and/or hepatic encephalopathy) and HCC diagnoses from 1996 to 2010. Multivariable Cox regression was used to examine adjusted hazard ratios [aHRs with 95% confidence interval (CIs)] of liver complications (first occurrence of ESLD or HCC) associated with hypothesized determinants and with increasing durations of HIV suppression (≤500 copies/mL). RESULTS: Among 3573 HIV/HBV patients with 13,790 person-years of follow-up, 111 liver complications occurred (incidence rate = 8.0 [95% CI: 6.6 to 9.7] events/1000 person-years). Rates of liver complication were increased with non-black/non-Hispanic race [aHR = 1.76 (1.13-2.74)], diabetes mellitus [aHR = 2.07 (1.20-3.57)], lower time-updated CD4 cell count [<200 cells/mm: aHR = 2.59 (1.36-4.91); 201-499 cells/mm: aHR = 1.75 (1.01-3.06) versus ≥500 cells/mm], heavy alcohol use [aHR = 1.58 (1.04-2.39)], and higher FIB-4 at start of follow-up [>3.25: aHR = 9.79 (5.73-16.74); 1.45-3.25: aHR = 3.20 (1.87-5.47) versus FIB-4 <1.45]. HIV suppression for ≥6 months was associated with lower liver complication rates compared with those with unsuppressed HIV [aHR = 0.56 (0.35-0.91)]. CONCLUSIONS: Non-black/non-Hispanic race, diabetes, lower CD4 cell count, heavy alcohol use, and advanced liver fibrosis were determinants of liver complications among HIV/HBV patients. Sustained HIV suppression should be a focus for HIV/HBV-coinfected patients to reduce the risks of ESLD/HCC.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".