作者：陈海晓1，陈静芸2，浦剑虹3，严晓云1，羌雯慧1，蔡红莉1

单位：

1.226001江苏省南通市第一人民医院全科　2.215000江苏省苏州市立医院老年科3.215000江苏省苏州市，苏州大学附属第一医院老年科

Units：

1.Department of General, Nantong First People's Hospital, Nantong 226001, China2.Department of Geriatrics, Suzhou Municipal Hospital, Suzhou 215000, China3.Department of Geriatrics, the First Affiliated Hospital of Soochow University, Suzhou 215000, China

关键词：

颈动脉狭窄；无症状性颈动脉狭窄；缺血性卒中；危险因素；列线图

Keywords：

Carotid stenosis; Asymptomatic carotid stenosis; Ischemic stroke; Risk factors; Nomogram

CLC：

R 543.4　

DOI：

10.12114/j.issn.1008-5971.2022.00.242

Funds：

2020年江苏省干部保健科研项目（BJ20009）

摘要：

目的　构建无症状性颈动脉狭窄患者发生缺血性卒中风险预测列线图模型，并验证其预测效能。方法　选取2019年在南通市第一人民医院体检的无症状性颈动脉狭窄患者214例作为研究对象。收集患者入院后首次检测的临床资料，采用LASSO回归和多因素Logistic回归分析探讨无症状性颈动脉狭窄患者发生缺血性卒中的影响因素。采用R 3.5.3软件和rms程序包构建列线图模型。采用一致性指数（CI ）、校准曲线和ROC曲线评估该列线图模型的预测效能。结果　214例患者中有41例发生缺血性卒中，发生率为19.2%；根据缺血性卒中发生情况将患者分为卒中组（n=41）和未卒中组（n=173）。多因素Logistic回归分析结果显示，高同型半胱氨酸血症、颈动脉狭窄程度≥50%且＜70%、斑块超声特点为非强回声和未使用他汀类药物治疗是无症状性颈动脉狭窄患者发生缺血性卒中的独立危险因素（P ＜0.05）。通过将原始数据重复抽样1 000次对该列线图模型进行内部验证，结果显示，CI 为0.804，校准曲线趋近于理想曲线。ROC曲线分析结果显示，该列线图模型预测无症状性颈动脉狭窄患者发生缺血性卒中的AUC为0.800〔95%CI （0.759，0.842）〕。结论　临床应重视高同型半胱氨酸血症、颈动脉狭窄程度≥50%且＜70%、斑块超声特点为非强回声和未使用他汀类药物治疗的无症状性颈动脉狭窄患者，警惕其发生缺血性卒中。本研究构建的列线图模型能够有效预测无症状性颈动脉狭窄患者发生缺血性卒中的风险。

Abstract：

Objective　To construct a nomogram model for predicting ischemic stroke risk in patients withasymptomatic carotid stenosis and verify its predictive efficiency. Methods　A total of 214 patients with asymptomatic carotidstenosis who underwent physical examination in Nantong First People's Hospital in 2019 were selected as the research subjects.The clinical data of the first detection after admission were collected. LASSO regression and multivariate Logistic regressionanalysis were used to explore the influencing factors of ischemic stroke in patients with asymptomatic carotid stenosis. Nomogrammodel was constructed by using R 3.5.3 software and the rms package. Concordance index (CI ) , calibration curve and ROCcurve were used to evaluate the predictive efficiency of the nomogram model. Results　Ischemic stroke occurred in 41 of 214patients, with an incidence rate of 19.2%, and they were divided into stroke group (n=41) and no stroke group (n=173) accordingto the occurrence of ischemic stroke. The results of multivariate Logistic regression analysis showed that hyperhomocysteinemia,carotid artery stenosis degree ≥ 50% and < 70%, non-hyperechoic plaque ultrasound and no statin treatment were independentrisk factors for ischemic stroke in patients with asymptomatic carotid stenosis (P < 0.05) . The nomogram model was internallyvalidated by repeated sampling of the original data 1 000 times, and the results showed that the CI was 0.804, and the calibrationcurve was close to the ideal curve. The results of ROC curve analysis showed that the AUC of the nomogram model for predictingischemic stroke risk in patients with asymptomatic carotid stenosis was 0.800 [95%CI (0.759, 0.842) ] . Conclusion　Clinicalattention should be paid to asymptomatic carotid stenosis patients with hyperhomocysteinemia, carotid artery stenosis degree of ≥50% and < 70%, non-hyperechoic plaque ultrasound and no statin therapy, and be alert to the occurrence of ischemic stroke inthe above patients. The nomogram model constructed in this study can effectively predict the risk of ischemic stroke in patientswith asymptomatic carotid stenosis.

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