In Patients with HIV-Infection, Chromium Supplementation Improves Insulin Resistance and Other Metabolic Abnormalities: A Randomized, Double-Blind, Placebo Controlled Trial
Bibliographic record
Abstract
Chromium is an essential micronutrient; chromium deficiency has been reported to cause insulin resistance, hyperglycemia and hyperlipidemia. The aim was to investigate the effect of chromium supplementation on insulin-resistance, other metabolic abnormalities, and body composition in people living with HIV. This was a randomized, double-blind, placebo-controlled trial. Fifty-two HIV-positive subjects with elevated glucose, lipids, or evidence of body fat redistribution, and who had insulin-resistance based on the calculation of homeostasis model of assessment (HOMA-IR > or = 2.5) were assessed. Subjects who were on insulin or hypoglycemic medications were excluded. Subjects were randomized to receive either 400 microg/day chromium-nicotinate or placebo for 16 weeks. Forty-six subjects, 23 in each group, completed the study. Fasting blood insulin, glucose, lipid profile and body composition were measured before and after intervention. Chromium was tolerated without side effects and resulted in a significant decrease in HOMA-IR (median (IQR) (pre:4.09 (3.02-8.79); post: 3.66 (2.40-5.46), p=0.004), insulin (pre: 102 (85-226); post: 99 (59-131) pmol/L, p=0.003), triglycerides, total body fat mass (mean+/-SEM) (pre: 17.3+/-1.7; post: 16.3+/-1.7 kg; p=0.002) and trunk fat mass (pre: 23.8+/-1.9; post: 22.7+/-2.0 %; p=0.008). Blood glucose, C-peptide, total, HDL and LDL cholesterol, and hemoglobin A1c remained unchanged. Biochemical parameters did not change in the placebo group except for LDL cholesterol which increased significantly. Body weight and medication profile remained stable throughout the study for both groups. In summary, chromium improved insulin resistance, metabolic abnormalities, and body composition in HIV+ patients. This suggests that chromium supplements alleviate some of the antiretroviral-associated metabolic abnormalities.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".