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甘油三酯-葡萄糖指数作为区分卒中病因亚型的生物标志物:一项基于医院的横断面研究。

Triglyceride-glucose index as a biomarker to differentiate stroke etiologic subtypes: a hospital-based cross-sectional study.

作者信息

Daoussi Nizar, Zemni Imen, Gouta Narjes, Saad Yasmine, Ben Dhia Rihab, Mhiri Mariem, Belghith-Sriha Asma, Frih-Ayed Mahbouba

机构信息

Neurology Department, University Hospital Fattouma Bourguiba, Monastir, Tunisia.

Community Health and Epidemiology Department, University Hospital Fattouma Bourguiba, Monastir, Tunisia.

出版信息

Biomark Med. 2025 Jan;19(1):23-29. doi: 10.1080/17520363.2024.2443382. Epub 2025 Jan 7.

DOI:10.1080/17520363.2024.2443382
PMID:39764663
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11731130/
Abstract

BACKGROUND

Accurate distinction between stroke etiologic subtypes is critical for physicians to provide tailored treatment. The triglyceride-glucose (TyG) index, a marker of insulin resistance, has been associated with stroke risk but its role in distinguishing stroke etiologic subtypes remains unclear. We aimed to assess the TyG index's ability to differentiate cardioembolic (CE) from non-cardioembolic (NCE) strokes.

METHODS

We studied 320 consecutive stroke patients in a cross-sectional analysis. Binary logistic regression was performed to analyze the association between the TyG index and the studied stroke subtypes. Receiver operating characteristic (ROC) curve analysis identified the optimal TyG index cutoff for CE vs. NCE differentiation.

RESULTS

TyG index correlated independently with NCE subtype (OR = 2.38; 95% CI = 1.52-3.73;  < 0.001). Logistic regression revealed increasing NCE stroke risk with higher TyG index quartiles. The ROC curve yielded an AUC of 0.636 (95% CI = 0.565-0.707;  < 0.001), with a cutoff of 8.8 (sensitivity = 68.8%, specificity = 57%).

CONCLUSION

The TyG index can be a useful biomarker in the differentiation between CE and NCE strokes.

摘要

背景

准确区分卒中病因亚型对于医生提供个性化治疗至关重要。甘油三酯-葡萄糖(TyG)指数作为胰岛素抵抗的一个指标,已被证实与卒中风险相关,但其在区分卒中病因亚型方面的作用仍不明确。我们旨在评估TyG指数区分心源性栓塞(CE)性卒中和非心源性栓塞(NCE)性卒中的能力。

方法

我们对320例连续的卒中患者进行了横断面分析。采用二元逻辑回归分析TyG指数与所研究的卒中亚型之间的关联。受试者工作特征(ROC)曲线分析确定了区分CE与NCE的最佳TyG指数临界值。

结果

TyG指数与NCE亚型独立相关(比值比=2.38;95%置信区间=1.52 - 3.73;P<0.001)。逻辑回归显示,随着TyG指数四分位数的升高,NCE卒中风险增加。ROC曲线下面积为0.636(95%置信区间=0.565 - 0.707;P<0.001),临界值为8.8(敏感性=68.8%,特异性=57%)。

结论

TyG指数可能是区分CE性卒中和NCE性卒中的一个有用的生物标志物。

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