Quantitative imaging in medicine and surgery · 2025
Comparison of six surrogate insulin resistance indices for predicting the accumulation of pericardial fat on noncontrast computed tomography.
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Zhou Shanshan, Xu Rongdi, Zhang Zhen, Gao Yiyuan, Li Gengxiao, Liu Shurong, Zou Huiting, Wang Cang, Zhan Yuefu, Zhou Yong, Han Ruijuan, Sun Kai
Аннотация
BACKGROUND: Insulin resistance is closely associated with pericardial fat. In this prospective study, we aimed to compare the utility of six surrogate insulin resistance indices, including the triglyceride glucose (TyG) index, TyG-waist circumference (TyG-WC), TyG-waist-to-height ratio (TyG-WHtR), lipid accumulation production (LAP), visceral adiposity index (VAI), and Chinese VAI (CVAI) in predicting pericardial fat accumulation on noncontrast computed tomography.
METHODS: The six surrogate insulin resistance indices (TyG, TyG-WC, TyG-WHtR, LAP, VAI, and CVAI) were calculated using their respective formulae. The pericardial fat volume (PFV) was obtained from noncontrast computed tomography scans and categorized into PFV-low (PFV-L) and PFV-high (PFV-H) via the Youden statistic according to the risk for atherosclerotic cardiovascular disease (ASCVD). A logistic regression model, receiver operating characteristic (ROC) curves, and generalized additive model were used for statistical analyses.
RESULTS: Overall, 2,735 adults were analyzed. The TyG, TyG-WC, TyG-WHtR, LAP, VAI, and CVAI were significantly higher in the PFV-H group than in the PFV-L group. All six insulin resistance surrogates showed significant positive correlations with PFV. The CVAI demonstrated the highest predictive value for assessing PFV, followed by TyG-WC, TyG-WHtR, LAP, TyG, and VAI. The CVAI was associated with the largest increase in PFV based on the original model [age, sex, diabetes, hypertension, hyperlipidemia, and estimated glomerular filtration rate (eGFR)] as compared to the other insulin resistance indices.
CONCLUSIONS: The TyG, TyG-WC, TyG-WHtR, LAP, VAI, and CVAI were positively associated with PFV in patients without overt cardiovascular diseases. The CVAI may effectively reflect PFV accumulation.
METHODS: The six surrogate insulin resistance indices (TyG, TyG-WC, TyG-WHtR, LAP, VAI, and CVAI) were calculated using their respective formulae. The pericardial fat volume (PFV) was obtained from noncontrast computed tomography scans and categorized into PFV-low (PFV-L) and PFV-high (PFV-H) via the Youden statistic according to the risk for atherosclerotic cardiovascular disease (ASCVD). A logistic regression model, receiver operating characteristic (ROC) curves, and generalized additive model were used for statistical analyses.
RESULTS: Overall, 2,735 adults were analyzed. The TyG, TyG-WC, TyG-WHtR, LAP, VAI, and CVAI were significantly higher in the PFV-H group than in the PFV-L group. All six insulin resistance surrogates showed significant positive correlations with PFV. The CVAI demonstrated the highest predictive value for assessing PFV, followed by TyG-WC, TyG-WHtR, LAP, TyG, and VAI. The CVAI was associated with the largest increase in PFV based on the original model [age, sex, diabetes, hypertension, hyperlipidemia, and estimated glomerular filtration rate (eGFR)] as compared to the other insulin resistance indices.
CONCLUSIONS: The TyG, TyG-WC, TyG-WHtR, LAP, VAI, and CVAI were positively associated with PFV in patients without overt cardiovascular diseases. The CVAI may effectively reflect PFV accumulation.