Predictive value of carotid artery contrast-enhanced ultrasound combined with clinical indicators in ischemic stroke patients

颈动脉增强超声联合临床指标对缺血性卒中患者的预测价值

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Abstract

OBJECTIVE: To assess the predictive significance of carotid artery contrast-enhanced ultrasound (CEUS) combined with the triglyceride glucose index (TyG index) and low-density lipoprotein (LDL) to high-density Lipoprotein (HDL) ratio in patients with ischemic stroke (IS). METHODS: This study included 130 patients admitted to the hospital from June 2021 to June 2023. All patients underwent carotid artery CEUS and were divided into two groups: the ischemic stroke group (IS, n = 73) and the non-ischemic stroke group (NIS, n = 57). Baseline characteristics of both groups were analyzed and compared to identify differences. Logistic regression analysis was performed to determine independent risk factors for IS. Receiver operating characteristic (ROC) curves were constructed to assess the predictive performance of CEUS classification, TyG index, LDL/HDL ratio, and their combination. RESULTS: Among the 130 patients, the IS group consisted of 73 individuals (53 males, 20 females), with an average age of 64.87 ± 10.55 years, while the NIS group included 57 patients (20 males, 37 females) with an average age of 63.12 ± 10.26 years. The IS group exhibited significantly higher CEUS classification, TyG index, and LDL/HDL ratio compared to the NIS group. Logistic regression analysis identified CEUS classification (OR 3.521, 95% CI 1.731-7.161, p = 0.001), TyG index (OR 3.851, 95% CI 1.129-13.142, p = 0.031), and LDL/HDL ratio (OR 2.957, 95% CI 1.321-6.622, p = 0.008) as independent risk factors for IS. The areas under the ROC Curve (AUC) for predicting IS were 0.871 for CEUS classification, 0.766 for TyG index, and 0.735 for LDL/HDL ratio. The combined application of these indicators yielded an AUC of 0.910, which was significantly higher than that of any single indicator. CONCLUSION: CEUS classification, TyG index, and LDL/HDL ratio are useful predictors of IS. Their combined use significantly enhances predictive accuracy.

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