Acute ischemic stroke (AIS) is caused by a sudden interruption of cerebral blood flow, leading to ischemic injury of brain tissue. Currently, the prediction, prevention, and treatment of AIS still primarily rely on traditional glycolipid markers. However, their sensitivity, specificity, and correlation with AIS need further improvement. There is an urgent need to optimize the combination of these parameters to enhance their efficacy in diagnosis and treatment of AIS.

To investigate the predictive value of non-conventional lipid indices (TG/HDL-C ratio, remnant cholesterol, etc) and triglyceride-glucose index (TyG index) for AIS, and their correlation with the severity of neurological injury.

A total of 313 newly diagnosed AIS patients admitted to the Department of Encephalopathy Center in Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine between April 2023 and May 2024 were enrolled as the stroke group. At the same time, 709 healthy control people from the same hospital were collected as the control group. General demographic and laboratory data were collected from both groups. Multivariate Logistic regression analysis was used to identify independent factors for AIS. Spearman rank correlation analysis was performed to evaluate the correlation between indicators such as TyG, FPG, TG/HDL-C and National Institutes of Health Stroke Scale (NIHSS) scores in AIS patients, and receiver operating characteristic (ROC) curves were used to assess the predictive value of individual and combined indicators (including TyG, FPG, and TG/HDL-C) for AIS.

No significant differences were observed between the two groups in terms of age, gender, LDL-C, or total cholesterol (TC) (P>0.05). However, statistically significant differences were found in the proportions of patients with a history of hypertension, diabetes, atrial fibrillation, hyperlipidemia, as well as in the levels of TG, HDL-C, RC, TyG index, TG/HDL-C ratio, non-high-density lipoprotein cholesterol (non-HDL-C), FPG, platelet count, and the platelet to HDL-C ratio (PHR) (P<0.05). Multivariate Logistic regression analysis identified the TyG (OR=2.710, 95%CI=1.192-6.160, P=0.017), TG/HDL-C (OR=1.765, 95%CI=1.033-3.014, P=0.037), FPG (OR=1.288, 95%CI=1.101-1.506, P=0.002), and PHR (OR=1.003, 95%CI=1.000-1.006, P=0.043) as independent influencing factors for AIS occurrence. Spearman rank correlation analysis revealed positive correlations between the TyG index, TG/HDL-C ratio, TG levels, and the NIHSS score in AIS patients (r_s=0.148, 0.140, 0.119, respectively; P<0.05). The results of the ROC curve showed that the AUCs of the TyG index, TG/HDL-C, TG, FPG, and PHR for predicting AIS were 0.712, 0.674, 0.646, 0.723, and 0.588, respectively. The AUC of the combined prediction of TyG index + FPG + TG + TG/HDL-C for AIS was 0.762, with a sensitivity of 64.0% and a specificity of 78.7%, indicating stable performance at multiple thresholds and strong overall discrimination ability, its Youden index was 0.426. Other combinations showed: FPG+TG had an AUC of 0.750, sensitivity of 74.0%, specificity of 69.3%, and a Youden index of 0.432; FPG+TG/HDL-C had an AUC of 0.761, sensitivity of 76.7%, specificity of 68.3%, and a Youden index of 0.450; FPG+PHR had an AUC of 0.740, sensitivity of 72.1%, specificity of 71.7%, and a Youden index of 0.438; FPG+TyG index+PHR had an AUC of 0.757, sensitivity of 69.3%, specificity of 74.0%, and a Youden index of 0.432. The results indicate that while the combination of TyG index+FPG+TG+TG/HDL-C demonstrates excellent comprehensive performance at specific thresholds.

The TyG index, TG/HDL-C, FPG, and PHR are independently associated with the risk of AIS occurrence, and can reflect the severity of neurological damage in AIS. The combined use of TyG index, FPG, TG and TG/HDL-C for diagnosing AIS yields a relatively high AUC, while the combination of FPG and TG/HDL-C demonstrates a higher Youden index.