Epicardial fat density, coronary artery disease and inflammation in people living with HIV
Bibliographic record
Abstract
Studies have shown an increased risk of coronary artery disease (CAD) in the human immunodeficiency virus (HIV) population. Epicardial fat (EF) quality may be linked to this increased risk. In our study, we evaluated the associations between EF density, a qualitative characteristic of fat, and inflammatory markers, cardiovascular risk factors, HIV-related parameters, and CAD. Our study was cross-sectional, nested in the Canadian HIV and Aging Cohort Study, a large prospective cohort that includes participants living with HIV (PLHIV) and healthy controls. Participants underwent cardiac computed tomography angiography to measure volume and density of EF, coronary artery calcium score, coronary plaque, and low attenuation plaque volume. Association between EF density, cardiovascular risk factors, HIV parameters, and CAD were evaluated using adjusted regression analysis. A total of 177 PLHIV and 83 healthy controls were included in this study. EF density was similar between the two groups (-77.4 ± 5.6 HU for PLHIV and -77.0 ± 5.6 HU for uninfected controls, P = .162). Multivariable models showed positive association between EF density and coronary calcium score (odds ratio, 1.07, P = .023). Among the soluble biomarkers measured in our study, adjusted analyses showed that IL2Rα, tumor necrosis factor alpha and luteizing hormone were significantly associated with EF density. Our study showed that an increase in EF density was associated with a higher coronary calcium score and with inflammatory markers in a population that includes PLHIV.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".