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TyG-derived indices like TyG-WC and CTI show stronger cardiovascular risk associations than the TyG indexNew ways to measure heart health risks using blood markers

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Key Takeaway
Note that TyG-derived indices, particularly TyG-WC and CTI, show stronger cardiovascular risk associations than the TyG index.

This meta-analysis of 80 observational studies evaluates the utility of triglyceride-glucose (TyG) indices, including TyG-BMI, TyG-WC, TyG-WHtR, and CTI, for assessing cardiovascular risk in populations with cardiovascular-kidney-metabolic (CKM) syndrome. The analysis compares these derived indices against the standard TyG index to determine their predictive value for mortality and disease incidence.

The meta-analysis found that TyG-derived indices generally showed stronger associations with cardiovascular outcomes than the standalone TyG index. Specifically, TyG-WC yielded the most pronounced risk for CVD mortality (RR = 1.52; 95% CI: 1.35 to 1.70). The CTI was associated with a 57% increase in incident CVD (RR = 1.57; 95% CI: 1.33 to 1.85), and TyG-BMI predicted a 51% risk increase for incident CVD (RR = 1.51; 95% CI: 1.36 to 1.67). A dose-response analysis of the TyG index revealed a non-linear U-shaped association with all-cause mortality (nadir = 8.90, P < 0.0001) and a significant overall association with CVD mortality (nadir = 8.91, P = 0.005).

Limitations noted include non-significant associations between TyG-BMI and mortality outcomes (P > 0.05). While these indices show promise for risk assessment in CKM populations, the clinical utility of TyG-BMI is limited. These findings suggest that TyG-derived indices may provide more robust risk stratification than the standard TyG index alone.

How this fits prior evidence

This meta-analysis addresses a gap in cardiovascular risk prediction by evaluating specific metabolic markers within the CKM syndrome population. While previous coverage noted that machine learning and multi-omics technologies can enhance cardiovascular diagnosis and personalized risk stratification, this study provides evidence for specific biochemical indices (TyG-WC, TyG-WHtR, and CTI) as potential tools for identifying high-risk patients.

Predicting heart health is about more than just one number. For people with cardiovascular, kidney, and metabolic issues, doctors need accurate ways to see who might be at the highest risk for a heart attack or stroke. A large review of 80 studies looked at how combining triglyceride (a type of fat) and glucose (blood sugar) into different formulas could improve these predictions.

Researchers found that specific combinations performed better than looking at the basic triglyceride-glucose index alone. For example, adding waist circumference to the calculation showed a much stronger link to heart disease deaths. Other variations, like combining the data with body mass index or waist-to-hip ratios, also showed clear links to increased risks of heart events.

While these new formulas provide more detail, they aren't perfect. One specific variation involving body mass index did not show a significant link to overall mortality. Because these findings come from observational studies, they show how certain markers are linked together rather than proving that one causes the other. Talk to your doctor about which markers best fit your personal health profile.

What this means for you:
Combining triglyceride and glucose with body measurements provides a clearer picture of heart disease risk.

Common questions

What is the TyG index?

The TyG index is a calculation that combines your triglyceride (fat) and glucose (sugar) levels. While it is a useful tool, this study found that adding other factors like waist circumference or body mass index to the formula can provide even more specific information about your risk for heart disease.

Which markers are best for predicting heart disease?

The study found that several variations performed well. The TyG-WC (waist circumference) calculation showed a strong link to heart disease deaths. Another method, called CTI, was linked to a 57% increase in new cases of heart disease, while the TyG-BMI method predicted a 51% risk increase.

Are these results guaranteed for every patient?

No, these findings are based on observational studies, which show associations rather than certainties. Additionally, some methods like TyG-BMI were less effective at predicting overall mortality. You should speak with your doctor to understand how these specific markers apply to your own health.

Study Details

Study typeMeta analysis
EvidenceLevel 1
PublishedAug 2026
View Original Abstract ↓
BackgroundThe associations of the triglyceride-glucose (TyG) index and its derived indices with the progression of cardiovascular-kidney-metabolic (CKM) syndrome remain poorly elucidated.MethodsWe conducted a systematic review and dose-response meta-analysis of 80 observational studies encompassing populations within CKM stages 0–3, evaluating TyG, TyG-BMI, TyG-WC, TyG-WHtR, and CTI for all-cause mortality, cardiovascular disease (CVD) mortality, and CVD incidence (including stroke, coronary heart disease, heart failure and major adverse cardiovascular events). A one-stage mixed-effects approach was used, supplemented by subgroup, meta-regression, leave-one-out, and trim-and-fill analyses.ResultsIn both continuous (per 1-SD increment) and categorical (highest vs. lowest) analyses, TyG-derived indices generally demonstrated stronger risk associations with target outcomes than TyG alone. Notably, CTI, TyG-WC, and TyG-WHtR exhibited higher risk associations. In the highest-category analysis, TyG-WC yielded the most pronounced risk for CVD mortality (RR = 1.52, 95% CI: 1.35–1.70, 95% PI: 1.26–1.82). CTI was associated with a 57% increase in incident CVD (RR = 1.57, 95% CI: 1.33–1.85, 95% PI: 1.00–2.46). Conversely, TyG-BMI showed non-significant associations with mortality-related outcomes (P > 0.05), though it predicted a 51% risk increase for incident CVD (RR = 1.51, 95% CI: 1.36–1.67, 95% PI: 1.05–2.16). Subgroup analysis indicated that these positive associations were pronounced in CKM stages 1–3 but entirely non-significant in stage 0 and the obesity subgroup had a significant impact on the risk of mortality. Dose-response analyses revealed a significant non-linear U-shaped association of the TyG index with all-cause mortality (Pnon-linearity < 0.0001; nadir = 8.90). For CVD mortality, the overall association was significant (Poverall = 0.005; nadir = 8.91), whereas a monotonic increasing trend was observed for CVD incidence (Poverall = 0.0014). In sensitivity analyses excluding participants with cancer or consumptive diseases at baseline, as well as those in CKM stage 0, the U-shaped patterns remained stable (mortality nadir shifted to 9.1).ConclusionsTyG-derived indices, particularly TyG-WC, TyG-WHtR, and CTI, show stronger risk associations than the TyG index for cardiovascular risk assessment in CKM populations, whereas the clinical utility of TyG-BMI is relatively limited. Moderate elevations in TyG were associated with lower mortality risk within a certain range, though the non-linear association was confirmed only for all-cause mortality.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/view/CRD420251111362, identifier CRD420251111362.
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