Value of estimated glucose disposal rate to detect prevalent left ventricular hypertrophy: implications from a general population. Issue 1 (2nd January 2023)

• Record Type: Journal Article
• Authors: Shi, Wenrui; Qin, Mu; Wu, Shaohui; Xu, Kai; Zheng, Qidong; Liu, Xu
• Is Part Of: Postgraduate medicine. Volume 135:Issue 1(2023)
• Page Start: 58
• Page End: 66
• Publication Date: 2023-01-02
• Subjects: Left ventricular hypertrophy -- insulin resistance -- estimated glucose disposal rate -- epidemiology; Medicine -- Periodicals; Medicine -- Periodicals; Medicine; Periodicals; 610.5
• DOI: 10.1080/00325481.2022.2131153
• Languages: English
• ISSNs: 0032-5481

Abstract

ABSTRACT: Background: Insulin resistance plays a pivotal role in developing left ventricular hypertrophy (LVH). Researchers have identified the estimated glucose disposal rate (eGDR) as a simple and cost-effective surrogate of insulin resistance. Our work aims to investigate the association between eGDR and the prevalent LVH and explore the incremental value of eGDR to detect prevalent LVH. Methods: The present work enrolled 3839 subjects from a cross-sectional survey conducted between October 2019 to April 2020 in the rural areas of southeastern China. eGDR was calculated based on waist-to-hip circumference ratio, hypertension, and glycated hemoglobin. Results: The prevalence of LVH was 17.30%. After adjusting demographic, anthropometric, laboratory, and medical history co-variates, each standard deviation increase of eGDR decreased a 29.6% risk of prevalent LVH. When dividing eGDR into quartiles, the top quartile had a 38.4% risk compared to the bottom quartile. Moreover, smooth curve fitting revealed that the association between eGDR and prevalent LVH was linear in the whole range of eGDR. Additionally, subgroup analysis demonstrated that our main finding was robust to age, sex, BMI, hypertension, and diabetes subgroups. Finally, ROC analysis exhibited a significant improvement by adding eGDR into LVH risk factors (0.780 vs. 0.803, P < 0.001), and category-free net reclassification index (0.702, P < 0.001) and integrated discrimination index (0.027, P < 0.001) also confirmed the improvement from eGDR to detect prevalent LVH. Conclusion: Our analysis revealed a linear, robust association between eGDR and prevalent LVH and demonstrated the incremental value of eGDR to optimize the detection of prevalent LVH.