Prevalence, Predictors, and Severity of Lean Nonalcoholic Fatty Liver Disease in Patients Living With Human Immunodeficiency Virus
Bibliographic record
Abstract
BACKGROUND: The burden of nonalcoholic fatty liver disease (NAFLD) is growing in people living with human immunodeficiency virus (HIV). NAFLD is associated with obesity; however, it can occur in normoweight (lean) patients. We aimed to investigate lean NAFLD in patients living with HIV. METHODS: We included patients living with HIV mono-infection from 3 prospective cohorts. NAFLD was diagnosed by transient elastography (TE) and defined as controlled attenuation parameter ≥248 dB/m, in absence of alcohol abuse. Lean NAFLD was defined when a body mass index was <25 kg/m2. Significant liver fibrosis was defined as TE ≥7.1 kPa. The presence of diabetes, hypertension, or hyperlipidemia defined metabolically abnormal patients. RESULTS: We included 1511 patients, of whom 57.4% were lean. The prevalence of lean NAFLD patients in the whole cohort was 13.9%. NAFLD affected 24.2% of lean patients. The proportions of lean NAFLD patients who were metabolically abnormal or had elevated alanine aminotransferase (ALT) were higher than among those who were lean patients without NAFLD (61.9% vs 48.9% and 36.7% vs 24.2%, respectively). Lean NAFLD patients had a higher prevalence of significant liver fibrosis than lean patients without NAFLD (15.7% vs 7.6%, respectively). After adjusting for sex, ethnicity, hypertension, CD4 cell count, nadir CD4 <200µ/L, and time since HIV diagnosis, predictors of NAFLD in lean patients were age (adjusted OR [aOR], 1.29; 95% confidence interval [CI], 1.04-1.59), high triglycerides (aOR, 1.34; 95% CI, 1.11-1.63), and high ALT (aOR, 1.15; 95% CI, 1.05-1.26), while a high level of high-density lipoprotein cholesterol was protective (aOR, 0.45; 95% CI, .26-.77). CONCLUSIONS: NAFLD affects 1 in 4 lean patients living with HIV mono-infection. Investigations for NAFLD should be proposed in older patients with dyslipidemia and elevated ALT, even if normoweight.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".