Fatty Liver Disease in a Prospective North American Cohort of Adults With Human Immunodeficiency Virus and Hepatitis B Virus Coinfection
Bibliographic record
Abstract
BACKGROUND: Hepatitis B virus (HBV) and fatty liver disease (FLD) are common in human immunodeficiency virus (HIV). Correlates of FLD and its relationship with alanine aminotransferase (ALT) were examined longitudinally in HIV-HBV coinfection. METHODS: From 28/4/2014-7/11/2018, 114 HIV-HBV adults had liver biopsy and were followed for a median of 3 years (ancillary study of Hepatitis B Research Network). Steatohepatitis was based on presence of steatosis, ballooning, and perisinusoidal fibrosis. FLD was defined as ≥5% steatosis and/or steatohepatitis. RESULTS: Median age was 49 years, 93% were male, 51% black, 93% had HIV RNA <400 copies/mL and 83% HBV DNA <1000 IU/mL. Thirty percent had FLD (20% steatosis, 10% steatohepatitis). Those with FLD had higher median triglyceride (171 vs 100 mg/dL, P < .01) and small, dense LDL (44 vs 29 mg/dL, P < .01) and lower HDL-2-C (9 vs 12 mg/dL, P = .001). After adjusting for age, sex, and alcohol use, white and other versus black race (ORs, 8.49 and 16.54, respectively), ALT (OR, 3.13/doubling), hypertension (OR, 10.93), hyperlipidemia (OR, 4.36), and diabetes family history (OR, 5.38) were associated with having FLD (all P < .05). Steatohepatitis or steatosis alone (vs none) was associated with higher ALT over time (1.93 and 1.34 times higher, respectively; P < .001), with adjustment for age, sex, and HBV DNA. CONCLUSIONS: About 30% with HIV-HBV coinfection had FLD including 10% with steatohepatitis. FLD was associated with non-black race, metabolic risks, an atherogenic lipid profile, and elevated ALT over time. Thus, identification of FLD and management of adverse metabolic profiles are critically important in HIV-HBV coinfection. Clinical Trial Registration. NCT01924455.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".