ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2024
Estimated Pulse Wave Velocity as a Novel Non-Invasive Biomarker for Metabolic Syndrome Among People Living with HIV.
Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Adropin and Endothelin-1 as Complementary Signals Associated with Early Vascular Aging in Middle-Aged Type 2 Diabetes.Diseases (Basel, Switzerland) · 2026Article
- Integrating Vascular Aging and Genetic Risk: The Combined Impact of Estimated Pulse Wave Velocity and Genetic Predisposition on Coronary Artery Disease.Journal of the American Heart Association · 2025Article
- Pathogenesis of HIV-Associated Metabolic Syndrome and Clinical Management Recommendations.International journal of general medicine · 2025Review
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: This study aims to investigate the relationship between estimated pulse wave velocity (ePWV) and metabolic syndrome (MetS) in people living with HIV (PLWH), proposing a novel and convenient predictor for early detection of MetS in PLWH. Patients and Methods: A total of 485 PLWH were enrolled. These participants were categorized into two groups based on the estimated pulse wave velocity (ePWV) level. Demographic and clinical data were collected to investigate the correlation between ePWV and MetS. Results: The cohort of 485 PLWH was categorized into high-ePWV and low-ePWV groups based on ePWV cutoff value of 10 m/s. We observed significant differences in components of MetS including triglycerides (TG, P < 0.05), HDL cholesterol (HDL-C, P < 0.01), systolic blood pressure (SBP, P < 0.001), diastolic blood pressure (DBP, P < 0.05), and fasting plasma glucose (FPG, P < 0.001) between the two groups. Furthermore, we employed receiver operating characteristic (ROC) curves to demonstrate the effectiveness of ePWV as a predictive indicator for MetS in PLWH (AUC = 0.739, P < 0.001). According to the ROC curve, the optimal cut-off value of ePWV was 7.4 m/s, and its sensitivity and specificity in diagnosing MetS in PLWH were 79.03% and 64.07%, respectively. Although the 7.4 m/s cutoff increased the false positive rate compared to the traditional cutoff, it significantly reduced the rate of missed diagnoses, effectively identifying 79.03% of PLWH with MetS. Conclusion: ePWV is a non-invasive and convenient novel biomarker with predictive capabilities for MetS in PLWH.
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