Metabolic abnormalities and viral replication are associated with biomarkers of vascular dysfunction in <scp>HIV</scp>‐infected children
Bibliographic record
Abstract
OBJECTIVES: HIV-infected children may be at risk for premature cardiovascular disease. We compared levels of biomarkers of vascular dysfunction in HIV-infected children (with and without hyperlipidaemia) with those in HIV-exposed, uninfected (HEU) children enrolled in the Pediatric HIV/AIDS Cohort Study (PHACS), and determined factors associated with these biomarkers. METHODS: A prospective cohort study was carried out. Biomarkers of inflammation [C-reactive protein (CRP), interleukin-6 (IL-6) and monocyte chemoattractant protein-1 (MCP1)], coagulant dysfunction (fibrinogen and P-selectin), endothelial dysfunction [soluble intracellular cell adhesion molecule-1 (sICAM), soluble vascular cell adhesion molecule-1 (sVCAM) and E-selectin], and metabolic dysfunction (adiponectin) were measured in 226 HIV-infected and 140 HEU children. Anthropometry, body composition, lipids, glucose, insulin, HIV disease severity, and antiretroviral therapy were recorded. RESULTS: The median ages of the children were 12.3 years in the HIV-infected group and 10.1 years in the HEU group. Body mass index (BMI) z-scores, waist and hip circumferences, and percentage body fat were lower in the HIV-infected children. Total and non-high-density lipoprotein (HDL) cholesterol and triglycerides were higher in HIV-infected children. HIV-infected children also had higher MCP-1, fibrinogen, sICAM and sVCAM levels. In multivariable analyses in the HIV-infected children alone, BMI z-score was associated with higher CRP and fibrinogen, but lower MCP-1 and sVCAM. Unfavourable lipid profiles were positively associated with IL-6, MCP-1, fibrinogen, and P- and E-selectin, whereas increased HIV viral load was associated with markers of inflammation (MCP-1 and CRP) and endothelial dysfunction (sICAM and sVCAM). CONCLUSIONS: HIV-infected children have higher levels of biomarkers of vascular dysfunction than do HEU children. Risk factors associated with higher biomarkers include unfavourable lipid levels and active HIV replication.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".