Triglyceride-glucose index as a prognostic marker after ischemic stroke or transient ischemic attack: a prospective observational study

Abstract Background Triglyceride-glucose (TyG) index has been proposed as a simple and credible surrogate for insulin resistance and an independent predictor of cardiovascular outcomes. Due to lack of data on TyG index in stroke, we aimed to evaluate the predictive value of the index for recurrent vascular event risk among stroke patients. Methods This was a prospective observational study, in which 866 patients (mean age, 70.1 years; male, 60.9%) with ischemic stroke (n = 781) or transient ischemic attack (n = 85) within 1 week of onset were consecutively enrolled and followed up for 1 year. The TyG index was calculated as ln (fasting triglycerides [mg/dL] × fasting glucose [mg/dL]/2). Patients were divided into 3 groups according to the tertile of TyG index levels: tertile 1, 9.01. The primary outcome was a composite of major adverse cardiovascular events (MACE), including nonfatal stroke, nonfatal acute coronary syndrome, and vascular death. Results The median TyG index was 8.74 (interquartile range, 8.34–9.16). Higher levels of TyG index were significantly associated with increased prevalence of ipsilateral extracranial carotid (P = 0.032) and intracranial (P = 0.003) atherosclerotic stenosis. There were significant differences in the MACE risk between the three groups (annual rate, 8.6%, 11.6%, and 17.3% in the tertile 1, tertile 2, tertile 3 groups, respectively; log-rank P = 0.005). After multivariable adjustments, the TyG index remains to be a significant predictor of MACE, with an adjusted hazard ratio for tertile 3 versus tertile 1 groups (95% confidence interval) of 2.01 (1.16–3.47). Similar results were also found for the risk of recurrent stroke. Conclusions TyG index is associated with cervicocerebral atherosclerosis and the MACE risk after a stroke, suggesting the potential value of TyG index to optimize the risk stratification of stroke patients. Trial registration URL: https://upload.umin.ac.jp . Unique identifier: UMIN000031913