Switch to a raltegravir‐based antiretroviral regimen in people with <scp>HIV</scp> and non‐alcoholic fatty liver disease: A randomized controlled trial
Bibliographic record
Abstract
INTRODUCTION: The effect of antiretroviral therapy (ART), particularly integrase strand transfer inhibitors (INSTIs), on non-alcoholic fatty liver disease (NAFLD) in people with HIV remains unclear. We evaluated the effect of switching non-INSTI backbone antiretroviral medications to raltegravir on NAFLD and metabolic parameters. MATERIALS AND METHODS: This was a single-centre, phase IV, open-label, randomized controlled clinical trial. People living with HIV with NAFLD and undetectable viral load while receiving a non-INSTI were randomized 1:1 to the switch arm (raltegravir 400 mg twice daily) or the control arm (continuing ART regimens not containing INSTI). NAFLD was defined as hepatic steatosis by controlled attenuation parameter ≥238 dB/m in the absence of significant alcohol use and viral hepatitis co-infections. Cytokeratin 18 was used as a biomarker of non-alcoholic steatohepatitis. Changes over time in outcomes were quantified as standardized mean differences (SMDs), and a generalized linear mixed model was used to compare outcomes between study arms. RESULTS: A total of 31 people with HIV (mean age 54 years, 74% male) were randomized and followed for 24 months. Hepatic steatosis improved between baseline and end of follow-up in both the switch (SMD -43.4 dB/m) and the control arm (-26.6 dB/m); the difference between arms was not significant. At the end of follow-up, aspartate aminotransferase significantly decreased in the switch arm compared with the control arm (SMD -9.4 vs. 5.5 IU/L). No changes in cytokeratin 18, body mass index, or lipids were observed between study arms. DISCUSSION: Switching to a raltegravir-based regimen improved aspartate aminotransferase but seemed to have no effect on NAFLD, body weight, and lipids compared with remaining on any other ART.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".