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2025 ; 24
(1
): 342
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Evaluation of a new TyG indicator, TyHGB, in predicting non-alcoholic fatty liver
disease: evidence from two independent populations
#MMPMID41131568
Zhao E
; Wang R
; Chen Y
; Xie H
; Gao Y
; Dong B
; Zhang C
Lipids Health Dis
2025[Oct]; 24
(1
): 342
PMID41131568
show ga
BACKGROUND: As non-alcoholic fatty liver disease (NAFLD) becomes increasingly
common and affects population health, simple and effective screening tools for
NAFLD are essential. The triglyceride high-density cholesterol-glucose body index
(TyHGB), a novel metabolic index, has shown promise for predicting metabolic
disorders. The objective of this research was to assess TyHGB's predictive
capability for NAFLD across two distinct cohorts. METHODS: This retrospective
study utilized data obtained from two independent cohorts: a Chinese hospital
cohort (n?=?181,241) and the National Health and Nutrition Examination Survey
(NHANES) cohort (n?=?3,286). TyHGB was computed according to the following
equation: triglyceride level/high-density lipoprotein cholesterol level?+?0.7 ×
fasting blood glucose level (mmol/L)?+?0.1 × body mass index (kg/m²). NAFLD was
diagnosed using ultrasonography. The TyHGB-NAFLD association was evaluated using
multivariable logistic regression analysis, restricted cubic spline methodology,
and receiver operating characteristic (ROC) curves. To establish the added
predictive capacity of TyHGB over the triglyceride-glucose (TyG) index, net
reclassification improvement (NRI) and integrated discrimination improvement
(IDI) were determined. RESULTS: In both cohorts, participants with higher TyHGB
values demonstrated a significantly higher prevalence of NAFLD. After full
adjustment for potential confounders, the odds ratios for NAFLD on comparing the
highest versus lowest quartiles of TyHGB were 12.22 (95% confidence interval
[CI]: 10.73-13.93) in the Chinese cohort and 3.17 (95% CI: 2.25-4.46) in the
NHANES cohort. Restricted cubic spline modeling demonstrated significant
nonlinear associations between TyHGB values and NAFLD risk in both populations (P
for nonlinearity?0.001). TyHGB demonstrated superior discriminative ability for
NAFLD in comparison with the TyG index, with area under the curve (AUC) values of
0.8410 versus 0.7995 in the Chinese cohort and 0.6492 versus 0.5952 in the NHANES
cohort (both P?0.001). Adding TyHGB to the baseline prediction models
significantly improved risk discrimination, with greater improvements than those
achieved by adding TyG (NRI: 0.0183, 95% CI: 0.015-0.0217; IDI: 0.0067, 95% CI:
0.0057-0.0076; both P?0.001). CONCLUSION: TyHGB demonstrated robust and
superior performance in predicting NAFLD in comparison with the established TyG
index across two diverse populations. Since TyHGB only requires routinely
measured clinical parameters, it represents a practical and equitable tool for
early NAFLD risk stratification across diverse healthcare settings, potentially
reducing health disparities in liver disease detection and enabling
cost-effective prevention strategies at the population level.