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血清微小核糖核酸及甘油三酯葡萄糖指数与急性缺血性脑卒中严重程度及预后的关系

Associations of serum microRNA and triglyceride-glucose index with severity and prognosis of acute ischemic stroke

    摘要
  • 摘要:
    目的 分析血清微小核糖核酸(miR)-15、miR-16、miR-17-5p、甘油三酯葡萄糖指数(TyG)与急性缺血性脑卒中(AIS)严重程度及预后的关系。
    方法 选取石家庄市中医院2023年4月—2024年4月就诊的136例AIS患者为研究对象, 分别采用改良Rankin量表(mRS)评分、美国国立卫生研究院卒中量表(NIHSS)评分评估患者预后、疾病严重程度。根据患者发病后3个月mRS评分将其分为预后不良组(mRS评分>2分，n=42)和预后良好组(mRS评分≤2分，n=94)。比较2组血清miR-15、miR-16、miR-17-5p、TyG、NIHSS评分; 采用Pearson相关性分析探讨血清miR-15、miR-16、miR-17-5p、TyG与NIHSS评分的相关性; 采用Logistic回归法分析AIS患者预后不良的危险因素; 采用受试者工作特征(ROC)曲线分析血清miR-15、miR-16、miR-17-5p、TyG、NIHSS评分预测AIS患者预后的价值。
    结果 预后不良组血清miR-15、miR-16、miR-17-5p、TyG、NIHSS评分高于预后良好组，差异有统计学意义(t=8.634、13.171、29.018、2.687、26.432, P < 0.05)。Pearson相关性分析显示，血清miR-15、miR-16、miR-17-5p、TyG与NIHSS评分均呈正相关(r=0.472、0.449、0.492、0.437, P < 0.05)。Logistic回归分析显示, miR-15OR(95%CI): 3.526(2.628~5.859)、miR-16OR(95%CI): 1.976(1.226~3.017)、miR-17-5pOR(95%CI): 1.828(1.294~3.428)、NIHSS评分OR(95%CI): 1.787(1.105~2.896)、TyGOR(95%CI): 1.886(1.233~3.284)、同型半胱氨酸OR(95%CI): 1.906(1.252~3.794)是AIS患者预后不良的危险因素(P < 0.05)。ROC曲线分析显示，血清miR-15、miR-16、miR-17-5p、TyG、NIHSS评分联合预测AIS患者预后不良的曲线下面积(AUC)为0.877，95%CI为0.820~0.948, 高于血清miR-15、miR-16、miR-17-5p、TyG、NIHSS评分单项检测的AUC，差异有统计学意义(Z=2.710、2.595、2.527、2.852、2.982, P=0.011、0.016、0.019、0.007、0.005)。
    结论 AIS患者血清miR-15、miR-16、miR-17-5p、TyG高表达与疾病严重程度及预后联系密切，联合检测血清miR-15、miR-16、miR-17-5p、TyG、NIHSS评分可提高对AIS患者预后不良的预测效能。

     

    Abstract:
    Objective To analyze the relationships of serum microRNA (miR)-15, miR-16, miR-17-5p, and triglyceride-glucose index (TyG) with severity and prognosis of acute ischemic stroke (AIS).
    Methods A total of 136 AIS patients admitted to the Shijiazhuang Hospital of Traditional Chinese Medicine from April 2023 to April 2024 were enrolled. Prognosis and disease severity were assessed using modified Rankin Scale (mRS) and National Institutes of Health Stroke Scale (NIHSS), respectively. Based on mRS scores at 3 months post-onset, patients were divided into poor prognosis group (mRS Score>2, n=42) and good prognosis group (mRS Score≤2, n=94). Serum levels of miR-15, miR-16, miR-17-5p, TyG, and NIHSS scores were compared between two groups. Pearson correlation analysis was used to evaluate associations of these biomarkers with NIHSS scores. Logistic regression was used to identify risk factors for poor prognosis, while receiver operating characteristic (ROC) curves was applied to assess the predictive value of individual and combined biomarkers.
    Results The poor prognosis group exhibited significantly higher serum miR-15, miR-16, miR-17-5p, TyG, and NIHSS scores than the good prognosis group (t=8.634, 13.171, 29.018, 2.687, 26.432; P < 0.05). Positive correlations were observed between these biomarkers and NIHSS scores (r=0.472, 0.449, 0.492, 0.437; P < 0.05). Logistic regression identified miR-15OR (95%CI): 3.526 (2.628 to 5.859), miR-161.976 (1.226 to 3.017), miR-17-5p1.828 (1.294 to 3.428), NIHSS score1.787 (1.105 to 2.896), TyG1.886 (1.233 to 3.284), and homocysteine1.906 (1.252 to 3.794)as independent risk factors for poor prognosis (P < 0.05). ROC analysis demonstrated that the combined model (miR-15, miR-16, miR-17-5p, TyG, and NIHSS) achieved superior predictive performance (AUC=0.877; 95%CI, 0.820 to 0.948) compared to individual biomarkers (Z>2.527, P < 0.05).
    Conclusion Elevated serum miR-15, miR-16, miR-17-5p, and TyG are closely associated with AIS severity and poor prognosis. The above indicators combined with NIHSS scores can enhance predictive accuracy for unfavorable outcomes.

     

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