Suling Chen,1,* Yuanhui Jiang,1,* Xiaoli Lin,1,* Hongjie Chen,1 Xiaoxuan Wu,2 Zhe Qian,3 Xuwen Xu,1 Huiqun Zhong,1 Jie Peng,1 Shaohang Cai1 

1Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 2Department of Communicable and Endemic Disease Control and Prevention, Haizhu District Center for Disease Control and Prevention, Guangzhou, People’s Republic of China; 3Second Department of Elderly Respiratory, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangdong Provincial Geriatrics Institute, Guangzhou, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Huiqun Zhong; Jie Peng, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, People’s Republic of China, Email lovely870821@163.com; pjie138@163.com

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.

Keywords: HIV/AIDS, highly active antiretroviral therapy, metabolic syndrome, estimated pulse wave velocity