Comparison of the triglyceride-glucose index and its modified indices for predicting mortality in advanced CLKM syndrome

This nationwide prospective cohort study included 1384 adults with advanced CLKM syndrome from NHANES 1999-2018. The associations between the TyG index, its modified variants, and all-cause mortality were assessed using weighted multivariable Cox proportional hazards models. Restricted cubic splines (RCS) were used to identify nonlinear associations. To compare predictive performance, C-index, net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated. RESULTS: Over a mean 56-month follow-up, 360 deaths were recorded. RCS revealed U-shaped associations (i.e., lower risk at intermediate levels and higher risk at both low and high levels) between TyG indices and mortality (P for nonlinear< 0.05), with inflection points at TyG = 9.56, TyG-WC = 1,039.11, TyG-WHtR = 5.17, and TyG-BMI = 215.85. At values below the inflection points, higher indices were associated with reduced mortality risk. Comparison based on the C-index, NRI, and IDI showed that the modified TyG indices did not outperform the original TyG in mortality prediction. Subgroup analyses confirmed consistency (P for interaction >0.05). CONCLUSION: In advanced CLKM syndrome, TyG indices exhibit U-shaped mortality association, revealing dual metabolic roles. The original TyG index performs comparably to anthropometry-enhanced variants, supporting its use as a parsimonious risk-stratification tool. Identified inflection points offer actionable thresholds for personalized management.

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Journal
Journal of Health Population and Nutrition
Published
2025-12-14
DOI
https://doi.org/10.1186/s41043-025-01187-5
Primary Topic
Genetic Syndromes and Imprinting
Type
article
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article

Comparison of the triglyceride-glucose index and its modified indices for predicting mortality in advanced CLKM syndrome

Huamei Li, Zhihua Huang, Ping Li, Dawei Wang et al.
Journal of Health Population and Nutrition
Genetic Syndromes and Imprinting
article

Comparison of the triglyceride-glucose index and its modified indices for predicting mortality in advanced CLKM syndrome

Huamei Li, Zhihua Huang, Ping Li, Dawei Wang, Junmao Wen, Jiahua Liang, Yueqiao Zhong
article en

Abstract

This nationwide prospective cohort study included 1384 adults with advanced CLKM syndrome from NHANES 1999-2018. The associations between the TyG index, its modified variants, and all-cause mortality were assessed using weighted multivariable Cox proportional hazards models. Restricted cubic splines (RCS) were used to identify nonlinear associations. To compare predictive performance, C-index, net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated. RESULTS: Over a mean 56-month follow-up, 360 deaths were recorded. RCS revealed U-shaped associations (i.e., lower risk at intermediate levels and higher risk at both low and high levels) between TyG indices and mortality (P for nonlinear< 0.05), with inflection points at TyG = 9.56, TyG-WC = 1,039.11, TyG-WHtR = 5.17, and TyG-BMI = 215.85. At values below the inflection points, higher indices were associated with reduced mortality risk. Comparison based on the C-index, NRI, and IDI showed that the modified TyG indices did not outperform the original TyG in mortality prediction. Subgroup analyses confirmed consistency (P for interaction >0.05). CONCLUSION: In advanced CLKM syndrome, TyG indices exhibit U-shaped mortality association, revealing dual metabolic roles. The original TyG index performs comparably to anthropometry-enhanced variants, supporting its use as a parsimonious risk-stratification tool. Identified inflection points offer actionable thresholds for personalized management.

Journal of Health Population and NutritionVol. 45(1)
Guangzhou University of Chinese Medicine (CN), State Administration of Traditional Chinese Medicine of the People's Republic of China (CN), First Affiliated Hospital of Guangzhou University of Chinese Medicine (CN)
Openalex Percentile: Top 58%
Genetic Syndromes and Imprinting
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