HIV-Associated Cardiovascular Disease Pathogenesis: An Emerging Understanding Through Imaging and Immunology
Bibliographic record
Abstract
Cardiac abnormalities were identified early in the epidemic of AIDS, predating the isolation and characterization of the etiologic agent, HIV. Several decades later, the causation and pathogenesis of cardiovascular disease (CVD) linked to HIV infection continue to be the focus of intense speculation. Before the widespread use of antiretroviral therapy, HIV-associated CVD was primarily characterized by HIV-associated cardiomyopathy linked to profound immunodeficiency. With increasing antiretroviral therapy use, viral load suppression, and establishment of immune competency, the effects of HIV on the cardiovascular system are more subtle. Yet, people living with HIV still face an increased incidence of cardiovascular pathology. Advances in cardiac imaging modalities and immunology have deepened our understanding of the pathogenesis of HIV-associated CVD. This review provides an overview of the pathogenesis of HIV-associated CVD integrating data from imaging and immunologic studies with particular relevance to the HIV population originating from high-endemic regions, such as sub-Saharan Africa. The review highlights key evidence gaps in the field and suggests future directions for research to better understand the complex HIV-CVD interactions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".