Zhongguo cuzhong zazhi (Feb 2024)
CTA结合临床特征预测中高海拔地区伴头颈部动脉粥样硬化的TIA患者脑梗死风险研究 CTA Combined with Clinical Characteristics to Predict the Risk of Cerebral Infarction in TIA Patients with Head and Neck Atherosclerosis at Middle and High Altitude Areas
Abstract
目的 基于头颈部CTA结合临床特征，探讨中高海拔地区伴头颈部动脉粥样硬化的TIA患者1年内发生脑梗死的危险因素，并构建风险预测模型，评价其预测效能。 方法 采用回顾性分析，连续纳入2018年1月—2021年9月青海省第五人民医院收治的TIA患者（居住海拔2000～3000 m），所有患者均经头颈部CTA证实存在动脉粥样硬化斑块。随访1年，根据是否发生脑梗死分为未梗死组与梗死组。首先对两组患者的临床资料和头颈部CTA检查结果进行单因素分析，筛选出有意义的变量，再通过多因素logistic回归分析脑梗死的独立影响因素，构建TIA后1年内发生脑梗死的风险预测模型以绘制ROC曲线。 结果 初步纳入患者111例。随访中出现9例失访，1例于外院放置颈动脉支架，1例发生硬膜下血肿，均不符合最终的纳入标准。最终纳入100例患者，其中梗死组26例，未梗死组74例。单因素分析显示梗死组ABCD2评分高于未梗死组[4.00（3.75～5.00)分 vs. 3.00（2.00～4.00）分，P=0.004]；梗死组高血压分级＞1级（69.23% vs. 41.89%，P=0.022）、具不稳定斑块（88.46% vs. 67.57%，P=0.039）、血管中重度狭窄（53.85% vs. 12.16%，P＜0.001）和不稳定斑块累及血管数＞1支（69.23% vs. 31.08%，P=0.001）的患者比例高于未梗死组，以上差异均有统计学意义。logistic回归分析显示，高血压分级＞1级、 ABCD2评分偏高及血管中重度狭窄是TIA后1年内发生脑梗死的独立危险因素，其风险预测模型为：P=1/[1+exp（﹣4.782+1.407×高血压分级+0.574×ABCD2评分+2.734×血管狭窄程度）]。该模型预测脑梗死的AUC为0.848（95%CI 0.763～0.933），敏感度为92.31%，特异度为70.27%。 结论 高血压分级＞1级、ABCD2评分偏高及血管中重度狭窄是中高海拔地区伴头颈部动脉粥样硬化的TIA患者1年内发生脑梗死的危险因素，三者联合构建的预测模型对脑梗死有良好的预测价值。 Abstract: Objective Based on the head and neck CTA combined with clinical characteristics to explore the risk factors of cerebral infarction within 1 year in patients with TIA from middle and high altitude areas with head and neck atherosclerosis, and construct a risk prediction model to evaluate its predictive effectiveness. Methods A retrospective analysis was performed to continuously select TIA patients (living at an altitude of 2000-3000 m) admitted to the Fifth People’s Hospital of Qinghai Province from January 2018 to September 2021. All patients were confirmed to have atherosclerotic plaques by CTA with head and neck. The patients were followed up for 1 year and divided into the non-infarction group and the infarction group according to whether there was a cerebral infarction. Firstly, the clinical data and CTA test results of the two groups of patients were analyzed by univariate analysis to screen out meaningful variables. Then, the independent influencing factors of cerebral infarction were analyzed by multivariate logistic regression, and the risk prediction model of cerebral infarction within 1 year after TIA was constructed to plot the ROC curve. Results A total of 111 patients were initially included. During follow-up, 9 cases were lost to follow-up, 1 case had carotid artery stenting in other hospital, and 1 case had subdural hematoma, all of which did not meet the final inclusion criteria. Finally, 100 patients were included, including 26 patients in the infarction group and 74 patients in the non-infarction group. Univariate analysis showed that the ABCD2 score of the infarction group was higher than that of the non-infarction group[4.00 (3.75-5.00) points vs. 3.00 (2.00-4.00) points, P=0.004]. The proportion of patients with hypertension grade>1 (69.23% vs. 41.89%, P=0.022), unstable plaque (88.46% vs. 67.57%, P=0.039), moderate to severe stenosis of vascular (53.85% vs. 12.16%, P1, high ABCD2 score and moderate to severe stenosis of vascular were independent risk factors for cerebral infarction within 1 year after TIA. The risk prediction model was P=1/[1+exp (-4.782+1.407×hypertension grade+0.574×ABCD2 score+2.734×vascular stenosis degree)]. The AUC value of this model was 0.848 (95%CI 0.763-0.933), the sensitivity was 92.31% and the specificity was 70.27%. Conclusions The risk factors for cerebral infarction within 1 year in TIA patients with head and neck atherosclerosis at middle and high altitude areas are hypertension grade>1, high ABCD2 score and moderate to severe stenosis of vascular. The prediction model constructed by the combination of these three factors together has good predictive value for cerebral infarction.
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