Nonalcoholic Fatty Liver Disease and the Development of Metabolic Comorbid Conditions in Patients With Human Immunodeficiency Virus Infection
Bibliographic record
Abstract
BACKGROUND: Cardiovascular and liver disease are main causes of death in people with human immunodeficiency virus (HIV) (PWH). In HIV-uninfected patients, nonalcoholic fatty liver disease (NAFLD) is associated with incident metabolic complications. We investigated the effect of NAFLD on development of metabolic comorbid conditions in PWH. METHODS: We included PWH undergoing a screening program for NAFLD using transient elastography. NAFLD was defined as a controlled attenuation parameter ≥248 dB/m with exclusion of other liver diseases. Incident diabetes, hypertension, dyslipidemia, and chronic kidney disease were investigated using survival analysis and Cox proportional hazards. RESULTS: The study included 485 HIV-monoinfected patients. During a median follow-up of 40.1 months (interquartile range, 26.5-50.7 months), patients with NAFLD had higher incidences of diabetes (4.74 [95% confidence interval, 3.09-7.27] vs 0.87 [.42-1.83] per 100 person-years) and dyslipidemia (8.16 [5.42-12.27] vs 3.99 [2.67-5.95] per 100 person-years) than those without NAFLD. With multivariable analysis, NAFLD was an independent predictor of diabetes (adjusted hazard ratio, 5.13; 95% confidence interval, 2.14-12.31) and dyslipidemia (2.35; 1.34-4.14) development. CONCLUSIONS: HIV-monoinfected patients with NAFLD are at higher risk of incident diabetes and dyslipidemia. Early referral strategies and timely management of metabolic risk may improve outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".