Endothelial dysfunction, a predictor of cardiovascular disease in HIV patients on antiretroviral therapy: A systematic review and meta-analysis
Bibliographic record
Abstract
Aim Although antiretroviral therapy (ART) is available, the rate of new HIV infections is alarming. With this trend, it is anticipated that the use of ART will continue to rise, potentially resulting in associated vascular disorders. Therefore, we aimed to examine the impact of ART on endothelial function in people living with HIV (PLHIV), a predictor of cardiovascular diseases. METHOD: A comprehensive search for evidence was made on PubMed and Scopus on May 06, 2023, following the Preferred Reporting Items for Systematic Review and Meta-analysis. Cochrane and Newcastle-Ottawa quality assessment scales were used to evaluate quality, while the metaHun web tool and Review Manager version 5.4.1 were used for analysis. Subgroup, sensitivity, and publication bias were conducted for each outcome measure. RESULTS: We identified 37 studies, including a sample size of 3700 with 2265 individuals on ART. The analyzed evidence showed a large significant effect of ART on vascular cell adhesion molecule-1, with a standardized mean difference (SMD) of -1.23 (95 % CI: -1.72, -0.74; p = 0.0013). Similarly, a significant medium effect of ART was observed on intercellular cell adhesion molecule-1 in PLHIV, with an SMD of -1.28 (95 % CI: -2.00, -0.56; p = 0.0231) compared to the control group. Furthermore, ART exhibited a significant but small effect on flow-mediated dilation (FMD) with an SMD of -0.40 (95 % CI: -0.62, -0.19, p = 0.0159). CONCLUSION: Our findings show an improved endothelial function in PLHIV on ART, as demonstrated by reduced adhesion molecules; however, ART exhibited a small effect on FMD, thus suggesting PLHIV on ART may still be at risk of endothelial dysfunction and further cardiovascular diseases.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".