Antiretroviral therapy as a cardiovascular disease risk factor: fact or fiction? A review of clinical and surrogate outcome studies
Bibliographic record
Abstract
PURPOSE OF REVIEW: The aim of this paper is to assess the contribution of antiretroviral therapy to cardiovascular disease, by evaluating relevant clinical and surrogate outcome studies. RECENT FINDINGS: A large proportion of patients receiving antiretroviral therapy develop insulin resistance and dyslipidemia, particularly if exposed to protease inhibitors. Recent findings from clinical outcome studies suggest that protease inhibitor-based therapy is associated with an increased risk of cardiovascular disease, with a consistent estimated increased risk of 1.16 to 1.17 for each additional year of protease inhibitor exposure. Antiretroviral therapy discontinuation, however, has also been linked with increased risk of cardiovascular disease. There are some data from clinical and surrogate outcome studies, that interventions addressing conventional risk factors and switching antiretroviral therapy may reduce cardiovascular disease risk. SUMMARY: Combination antiretroviral therapy in general, and protease inhibitor-based antiretroviral therapy in particular, is associated with an increased risk of cardiovascular disease. This risk is likely mediated, in part, by changes in blood lipids. The absolute risk of cardiovascular disease for the individual patient depends on his or hers composite risk profile. It is becoming increasingly important to carry out an adequate cardiovascular disease risk assessment in each patient, in order to identify patients in need of specific interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".