Application of TyG index and carotid ultrasound parameters in the prediction of ischemic stroke

Huimin Guo ^1,2 Sen Wang ¹ Haizheng Wang ¹ Li Feng ^1*

• ¹ Department of Medical Ultrasound, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qian Foshan Hospital, Jinan, Shandong Province, China
• ² School of Clinical Medicine, Jining Medical University, Jining, Shandong, China

Objective The triglyceride - glucose (TyG) index is an independent risk factor for ischemic stroke (IS). Regarding the role of carotid ultrasound in the risk assessment of IS, the focus has shifted from merely concentrating on the degree of stenosis to paying more attention to the status of carotid plaques. However, there are limited studies on combining clinical indicators such as the TyG index with carotid ultrasound parameters to assess the risk of IS. We aim to explore the role of combining these two types of indicators in the risk assessment of IS. Methods This study included 145 patients with IS and 99 non - ischemic stroke (NIS) patients diagnosed by magnetic resonance imaging (MRI) from January 2020 to June 2024. Clinical indicators such as the TyG index and carotid ultrasound parameters were collected. Univariate (multivariate) logistic regression analysis and receiver operating characteristic (ROC) curve analysis were conducted on the data using SPSS 26 to evaluate the effectiveness of combining clinical indicators with carotid ultrasound parameters in predicting the risk of IS. Results Univariate logistic regression analysis (ULR) showed that age, gender, clinical indicators such as the TyG index, cystatin C (Cys C), the presence or absence of carotid plaques, plaque location, carotid intima - media thickness (CIMT), and the length and thickness of the largest plaque were significantly associated with IS (P < 0.05). The area under the receiver operating characteristic curve (AUC) of the TyG index for predicting IS was 0.645 (P < 0.001). The optimal cut - off value was 8.28, with a sensitivity of 0.83 and a specificity of 0.63. Multiple risk prediction models were constructed and analyzed by ROC curves. Model 1, which integrated traditional clinical indicators, the TyG index, and carotid ultrasound parameters, performed best (AUC = 0.932) (P < 0.001). Conclusion This study confirms that combining the TyG index with carotid ultrasound parameters is of great significance in predicting the risk of IS. The predictive ability of the TyG index alone is limited, and Model 1 integrating multiple indicators has the best predictive effect, which can provide a reference for clinical practice.