Bibliographic record
Abstract
PURPOSE OF REVIEW: Since the advent of highly active antiretroviral treatment, accelerated atherosclerosis resulting in coronary artery disease (CAD) has become an area of increasing concern among patients infected with HIV. As CAD has replaced myocarditis and opportunistic infection as the most common cause of heart failure in this population, it is necessary to re-evaluate the specific risks of cardiovascular disease in HIV-infected patients taking into consideration the processes driving atherogenesis. RECENT FINDINGS: Recent data illustrating that atazanavir is not associated with an increased risk of CAD argue against a class-wide association of protease inhibitors in HIV treatment and adverse cardiovascular outcomes. C-C chemokine receptor-type 5 has been identified as a potential target for pharmacological therapy to manage the process of atherosclerosis while simultaneously having an antiretroviral effect. Additionally, as the use of statins has recently been associated with new-onset diabetes in the general population, further investigation of this risk in HIV-infected patients is necessary. SUMMARY: HIV-infected patients have an increased risk of CAD and subsequently heart failure. This is likely because of a confluence of several factors including: conventional risk factors, HIV-specific processes driving inflammation, coagulatory pathway and endothelial dysfunction. The benefits of antiretroviral drugs in terms of overall survival rates outweigh the risks of dyslipidemia. The focus of the management of cardiovascular risk remains in the domains of primary and secondary prevention. More accurate risk stratification, which accounts for HIV-specific risk factors, is now increasingly warranted.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".