Fibroscan–Aspartate Aminotransferase Score Predicts Liver-Related Outcomes, but Not Extrahepatic Events, in a Multicenter Cohort of People With Human Immunodeficiency Virus
Bibliographic record
Abstract
BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is frequent in people with human immunodeficiency virus (PWH). The Fibroscan-aspartate aminotransferase (FAST) score was developed to identify patients with nonalcoholic steatohepatitis (NASH) and significant fibrosis. We investigated prevalence of NASH with fibrosis and the value of FAST score in predicting clinical outcomes in PWH. METHODS: Transient elastography (Fibroscan) was performed in PWH without viral hepatitis coinfection from 4 prospective cohorts. We used FAST >0.35 to diagnose NASH with fibrosis. Incidence and predictors of liver-related outcomes (hepatic decompensation, hepatocellular carcinoma) and extrahepatic events (cancer, cardiovascular disease) were evaluated through survival analysis. RESULTS: Of the 1472 PWH included, 8% had FAST >0.35. Higher body mass index (adjusted odds ratio [aOR], 1.21 [95% confidence interval {CI}, 1.14-1.29]), hypertension (aOR, 2.24 [95% CI, 1.16-4.34]), longer time since HIV diagnosis (aOR, 1.82 [95% CI, 1.20-2.76]), and detectable HIV RNA (aOR, 2.22 [95% CI, 1.02-4.85]) were associated with FAST >0.35. A total of 882 patients were followed for a median of 3.8 years (interquartile range, 2.5-4.2 years). Overall, 2.9% and 11.1% developed liver-related and extrahepatic outcomes, respectively. Incidence of liver-related outcomes was higher in patients with FAST >0.35 versus FAST ≤0.35 (45.1 [95% CI, 26.2-77.7] vs 5.0 [95% CI, 2.9-8.6] per 1000 person-years). FAST >0.35 remained an independent predictor of liver-related outcomes (adjusted hazard ratio, 4.97 [95% CI, 1.97-12.51]). Conversely, FAST did not predict extrahepatic events. CONCLUSIONS: A significant proportion of PWH may have NASH with significant liver fibrosis. FAST score predicts liver-related outcomes and can help management of this high-risk population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".