Triglyceride glucose index and its combination with the Get with the Guidelines-Heart Failure score in predicting the prognosis in patients with heart failure - Han, Su; Wang, Chuanhe; Tong, Fei; Li, Ying; Li, Zhichao; Sun, Zhaoqing; Sun, Zhijun (Frontiers in Nutrition, 2022)
Background Heart failure (HF) is associated with generalized insulin resistance (IR). Recent studies demonstrated that triglyceride glucose (TyG) is an effective alternative index of IR. However, the relationship between the TyG index and in-hospital mortality in patients with HF is unclear. In the present study, we aimed to clarify the association between the TyG index and in-hospital mortality in patients with HF. Methods A retrospective study consisting of 4,411 patients diagnosed with HF from 2015 to 2018 was conducted. All-cause mortality during hospitalization was the primary endpoint. The association between the TyG index and in-hospital mortality was assessed using the logistic regression analysis. Results The risk of in-hospital mortality was significantly associated with increased TyG index (OR: 1.886, 95% CI: 1.421–2.501, p < 0.001) under logistic regression with multivariable adjustment. When divided into three groups based on the TyG index, Tertile 3 demonstrated significantly higher in-hospital mortality than the other two Tertiles (OR: 2.076, 95% CI: 1.284–3.354, p = 0.001). Moreover, the TyG index improved the prediction efficiency of the Get with the Guidelines-Heart Failure (GWTG-HF) score (absolute integrated discrimination improvement = 0.006, p < 0.001; category-free net reclassification improvement = 0.075, p = 0.005). In subgroup analysis, the TyG index exhibited similar predictive performance of in-hospital mortality when groups were stratified based on type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD). Conclusion TyG is a potential index for predicting in-hospital mortality in patients with HF, independent of T2DM or CAD status. The TyG index may be combined with the GWTG-HF score to further improve its predictive efficacy.