A Prospective Study of Body Fat Redistribution, Lipid, and Glucose Parameters in HIV-Infected Patients Initiating Combination Antiretroviral Therapy
Bibliographic record
Abstract
PURPOSE: To prospectively determine incidence, prevalence, and extent of lipodystrophy (LD) and associated metabolic changes. METHOD: This was a prospective cohort study. Body habitus changes were determined by anthropometrics, photography, and regional dual-energy X-ray absorptiometry (DXA) scan. Metabolic parameters included triglyceride (TG), total (TC), LDL and HDL cholesterol, glucose, and insulin. RESULTS: 68 patients were included. 51 (75%) received protease inhibitor (PI)-based and 17 (25%) non-nucleoside reverse transcriptase inhibitor (NNRTI)-based antiretroviral therapy (ARV) and 90% a thymidine analogue. Statistically significant increases in TC, TG, LDL, and HDL by 12 months developed on PI but only in TC for NNRTI. At 24 months, on DXA scanning, there were no statistically significant changes in median limb or total body fat on NNRTI but a statistically significant decrease in limb fat on PI (p = .01). There was considerable individual variation with overall 3 (7%) patients having >20% increases and 16 (36%) with >20% decreases in limb fat and 6 (14%) having >20% increases and 7 (16%) with >20% decreases in total body fat. CONCLUSIONS: Lipid changes occurred early and progressed. Median changes in body fat were minor and more common on PI, but individual variation in change was large, challenging the use of medians or threshold changes to predict impact of different ARV agents.
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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 | 0.001 |
| 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 | 0.000 |
| 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".