| 摘要: |
| ［摘要］ 目的 分析血清同型半胱氨酸（Hcy）、超敏C反应蛋白（hs-CRP）/白蛋白（ALB）比值及甘油三酯-葡萄糖（TyG）指数对进展性缺血性脑卒中（PIS）发生的影响，并构建列线图模型。方法 回顾性分析2020年1月至12月巴彦淖尔市医院神经内科收治的331例急性缺血性脑卒中（AIS）患者的临床资料，根据患者住院期间病情进展情况将其分为PIS组（92例）和非PIS组（239例）。采用多因素logistic回归分析影响PIS发生的因素，并基于筛得指标构建预测PIS发生的列线图模型。采用受试者工作特征（ROC）曲线、Hosmer-Lemeshow检验、校正曲线以及决策曲线分析（DCA）评估列线图模型的预测效能及应用价值。 结果 多因素logistic回归分析结果显示，以小动脉闭塞型为参照，大动脉粥样硬化型［OR（95%CI）=6.894（3.306～14.375）］是促进PIS发生的独立危险因素（P<0.05）；以血管轻度狭窄为参照，血管重度狭窄［OR（95%CI）=5.105（2.168～12.018）］以及血管闭塞［OR（95%CI）=18.599（4.696～73.671）］是促进PIS发生的独立危险因素（P<0.05）；较高的入院时NIHSS评分［OR（95%CI）=1.146（1.032～1.271）］、Hcy［OR（95%CI）=1.027（1.003～1.051）］、hs-CRP/ALB比值［OR（95%CI）=1.064（1.029～1.101）］和TyG指数［OR（95%CI）=1.520（1.044～2.214）］以及有糖尿病史［OR（95%CI）=2.631（1.294～5.348）］是促进PIS发生的独立危险因素（P<0.05）。基于这些指标构建预测PIS发生的列线图模型。ROC曲线分析结果显示，该模型具有较高的预测效能［AUC（95%CI）=0.910（0.872～0.948）］，灵敏度为85.87%，特异度为87.87%。Hosmer-Lemeshow检验结果显示，该模型预测值和实际观测值之间无显著差异（P=0.300）。校正曲线分析结果显示，模型校正曲线与理想曲线一致性良好。DCA结果显示，阈概率值为0.05～0.99时，使用该模型预测AIS患者发生PIS的净获益较高。结论 较高的Hcy、hs-CRP/ALB比值及TyG指数水平是促进PIS发生的危险因素。本研究构建的列线图模型可有效预测PIS的发生，有助于临床医师及早识别高风险患者。 |
| 关键词: 进展性缺血性脑卒中 同型半胱氨酸 超敏C反应蛋白 白蛋白 甘油三酯-葡萄糖指数 列线图 |
| DOI：10.3969/j.issn.1674-3806.2026.03.14 |
| 分类号:R 743 |
| 基金项目:内蒙古自然科学基金面上项目（编号：2020MS08061）；巴彦淖尔市科技计划项目（编号：K202136） |
|
| Effects of Hcy, hs-CRP to ALB ratio and TyG index on the occurrence of progressive ischemic stroke and construction of a nomogram model |
|
QING Yun1, HE Wen2
|
|
1.Bayannur Clinical College, Inner Mongolia Medical University, Bayannur 015000, China; 2.The First Department of Neurology, Bayannur Hospital, Bayannur 015000, China
|
| Abstract: |
| ［Abstract］ Objective To analyze the effects of homocysteine(Hcy), high-sensitivity C-reactive protein to albumin ratio(hs-CRP/ALB) and triglyceride-glucose(TyG) index on the occurrence of progressive ischemic stroke(PIS), and to construct a nomogram model. Methods A retrospective analysis was conducted on the clinical data of 331 patients with acute ischemic stroke(AIS) who were admitted to the Department of Neurology of Bayannur Hospital from January 2020 to December 2020. According to the disease progression of the patients during hospitalization, they were divided into PIS group(92 patients) and non-PIS group(239 patients). Multivariate logistic regression was used to analyze the factors influencing the occurrence of PIS, and a nomogram model for predicting the occurrence of PIS was constructed based on the indicators obtained through screening. The predictive efficacy and application value of the nomogram model were evaluated by using receiver operating characteristic(ROC) curve, Hosmer-Lemeshow test, calibration curve and decision curve analysis(DCA). Results The results of multivariate logistic regression analysis showed that, taking small artery occlusion type as the reference, large artery atherosclerosis type［OR(95%CI)=6.894(3.306-14.375)］ was an independent risk factor promoting the occurrence of PIS(P<0.05); and taking mild vascular stenosis as the reference, severe vascular stenosis［OR(95%CI)=5.105(2.168-12.018)］ and vascular occlusion［OR(95%CI)=18.599(4.696-73.671)］ were independent risk factors promoting the occurrence of PIS(P<0.05); and higher National Institutes of Health Stroke Scale(NIHSS) scores at admission［OR(95%CI)=1.146(1.032-1.271)］, higher Hcy［OR(95%CI)=1.027(1.003-1.051)］, higher hs-CRP/ALB［OR(95%CI)=1.064(1.029-1.101)］ and higher TyG index［OR(95%CI)=1.520(1.044-2.214)］ as well as a history of diabetes［OR(95%CI)=2.631(1.294-5.348)］ were independent risk factors for promoting the occurrence of PIS(P<0.05). Based on the above indicators, a nomogram model for predicting the occurrence of PIS was constructed. The results of ROC curve analysis showed that the constructed model had high predictive efficacy［AUC(95%CI)=0.910(0.872-0.948)］, with a sensitivity of 85.87% and a specificity of 87.87%. The results of Hosmer-Lemeshow test showed that there was no significant difference between the predicted value of the model and its actual observed value(P=0.300). The results of calibration curve analysis showed that the calibration curve of the model was in good consistency with its ideal curve. The results of DCA showed that when the threshold probability values ranged from 0.05 to 0.99, the net benefit of using the model to predict the occurrence of PIS in the AIS patients was relatively high. Conclusion Higher levels of Hcy, hs-CRP/ALB and TyG index are risk factors promoting the occurrence of PIS. The nomogram model constructed in this study can effectively predict the occurrence of PIS, which is helpful for clinicians to identify patients at high risk as soon as possible. |
| Key words: Progressive ischemic stroke(PIS) Homocysteine(Hcy) High-sensitivity C-reactive protein(hs-CRP) Albumin(ALB) Triglyceride-glucose(TyG) index Nomogram |
