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Published on: January 7, 2018
Triglyceride-Glucose Index and Mortality Risk in the General Population: A Systematic Review and Meta-analysis of
D'Elia Lanfranco1,2, Saverio Stranges3,4,5,6, Ersilia La Fata7
1Department of Clinical Medicine and Surgery, "Federico II" University of Naples Medical School, Via S. Pansini, 5, 80131, Naples, Italy. lanfranco.delia@unina.it.
Introduction:
Insulin resistance (IR) is a major determinant of cardiovascular disease and mortality, yet its direct measurement is limited by the need for insulin assays. The triglyceride-glucose (TyG) index has emerged as a simple and inexpensive surrogate marker of IR, but its prognostic relevance for mortality remains uncertain due to the heterogeneity of available studies.
Aim:
This study aimed to: (i) evaluate the predictive value of the TyG index for all-cause and cardiovascular mortality risk in the general population; (ii) assess the shape and magnitude of the dose-response relationship; and (iii) identify the most appropriate threshold for mortality risk prediction.
Methods:
A systematic review and dose-response meta-analysis was conducted, including prospective cohort studies that assessed baseline TyG and subsequent mortality. Random-effects models were used to pool hazard ratios, and restricted cubic splines were applied to examine potential non-linearity in the dose-response relationship.
Results:
Twelve studies comprising 14 independent cohorts (≈10.8 million participants) were included. Each one-unit increase in TyG was associated with a 14% higher risk of all-cause mortality and a 16% higher risk of cardiovascular mortality starting from 6.9 units (or 3.79 units in the alternative scale). Associations were linear and consistent across sensitivity analyses. There was a significant heterogeneity among studies, but no evidence of publication bias.
Conclusion:
The TyG index independently and linearly predicts all-cause and cardiovascular mortality, supporting its potential role as a clinically useful, low-cost marker for early cardio-metabolic risk stratification in population-based settings.
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