目的 基于临床特征及影像学探讨椎动脉颅内段动脉粥样硬化狭窄的影响因素。 方法 本研究采用回顾性分析，选取2021年1月至2025年6月因头晕、眩晕等后循环缺血症状就诊，或接受常规脑血管评估，并同时完成脑-颈动脉超声及CT血管造影（CTA）检查患者216例。以CTA为诊断标准，将椎动脉颅内段狭窄率≥ 50%者纳入病例组（62例），将无狭窄或狭窄率< 50%者纳入对照组（154例）。比较两组患者的临床资料、超声血流动力学参数及斑块特征。将单因素分析中P < 0.05的变量纳入多因素logistic回归模型，筛选独立影响因素。 结果 病例组椎动脉收缩期峰值流速及椎动脉舒张末期流速均显著大于对照组（P < 0.05），椎动脉管径显著小于对照组（P < 0.05）。病例组有吸烟史、合并高血压、合并糖尿病、偏心型斑块的比例均显著高于对照组（均P < 0.05）。病例组低密度脂蛋白水平及斑块负荷也显著大于对照组（P < 0.05）。单因素分析显示，两组在以上指标中差异有统计学意义（均P < 0.05），将单因素分析有意义的变量纳入多因素logistic回归分析，结果显示，有吸烟史（OR = 3.340，95%CI：1.258 ~ 8.865）、低密度脂蛋白水平升高（OR = 2.392，95%CI：1.233 ~ 4.639）、合并高血压（OR = 2.630，95%CI：1.108 ~ 6.242）、合并糖尿病（OR = 2.863，95%CI：1.302 ~ 6.296）、偏心型斑块（OR = 2.649，95%CI：1.398 ~ 5.018）、斑块负荷大（OR = 2.482，95%CI：1.267 ~ 4.861）均为椎动脉颅内段动脉粥样硬化狭窄的独立影响因素（均P < 0.05）。据此构建模型，logit（P） = 0.685 + 1.206 × 吸烟史 + 0.872 × 低密度脂蛋白水平升高 + 0.967 × 合并高血压 + 1.052 × 合并糖尿病 + 0.974 × 偏心型斑块 + 0.909 × 斑块负荷大。当logit（P）> 0.648时，AUC = 0.891（95%CI：0.842 ~ 0.930），χ² = 15.320，敏感度、特异度为83.87%、83.12%。 结论 本研究提示，吸烟史、高血压、糖尿病、高低密度脂蛋白胆固醇（LDL-C）水平及偏心性、高负荷斑块是椎动脉颅内段狭窄的独立影响因素。上述指标构建logistic模型拟合良好，对椎动脉颅内段动脉粥样硬化狭窄具有较高的预测价值。临床对于具备上述特征的患者，应加强椎动脉颅内段的影像学筛查与风险评估。

Objective Based on clinical features and imaging data， the influencing factors of atherosclerotic stenosis in the intracranial segment of the vertebral artery were explored. Methods This study adopted a retrospective analysis approach. It selected 216 patients who either visited the hospital because of symptoms like dizziness and vertigo associated with posterior circulation ischemia or underwent routine cerebrovascular assessment. These patients simultaneously completed brain-cervical artery ultrasound and CT Angiography （CTA） examinations between January 2021 and June 2025. According to the diagnostic criteria of CTA， patients with a stenosis rate of ≥ 50% in the intracranial segment of the vertebral artery were included in the case group （62 cases）， whereas those without stenosis or with a stenosis rate < 50% were included in the control group （154 cases）. The clinical data， ultrasound hemodynamic parameters， and plaque characteristics of the two groups were compared. Variables with P < 0.05 in the univariate analysis were incorporated into the multivariate logistic regression model to screen out independent influencing factors. Results The peak systolic velocity and the end-diastolic velocity of the vertebral artery in the case group were significantly higher than those in the control group （P < 0.05）. Meanwhile， the diameter of the vertebral artery in the case group was significantly smaller than that in the control group （P < 0.05）. The proportion of patients with a smoking history， hypertension， diabetes， and eccentric plaques in the case group was significantly higher than that in the control group （all P < 0.05）. The levels of low-density lipoprotein and plaque burden in the case group were also significantly higher than those in the control group （P < 0.05）. Single-factor analysis indicated that there were statistically significant differences in the above indicators between the two groups （all P < 0.05）. The variables with significant meanings from the single-factor analysis were then included in the multivariate Logistic regression analysis. The results demonstrated that having a smoking history （OR = 3.340， 95%CI： 1.258 - 8.865）， elevated low-density lipoprotein levels （OR = 2.392， 95%CI： 1.233 - 4.639）， hypertension （OR = 2.630， 95%CI： 1.108 - 6.242）， diabetes （OR = 2.863， 95%CI： 1.302 - 6.296）， eccentric plaques （OR = 2.649， 95%CI： 1.398 - 5.018）， and large plaque burden （OR = 2.482， 95%CI： 1.267 - 4.861） were all independent influencing factors of atherosclerotic stenosis of the intracranial segment of the vertebral artery （all P < 0.05）. Based on this， a model was constructed as follows： logit（P） = 0.685 + 1.206 × smoking history + 0.872 × increase in low-density lipoprotein level + 0.967 × co-occurrence of hypertension + 1.052 × co-occurrence of diabetes + 0.974 × eccentric plaque + 0.909 × large plaque load. When logit（P） > 0.648， the AUC is 0.891 （95%CI： 0.842 - 0.930）， χ² = 15.320， and the sensitivity and specificity are 83.87% and 83.12% respectively. Conclusions This study demonstrates that a history of smoking， hypertension， diabetes， elevated LDL-C levels， eccentric and high-load plaques are independent influencing factors for stenosis of the intracranial segment of the vertebral artery. Based on these indicators， a logistic model was successfully constructed. This model fits well and has a high predictive value for atherosclerotic stenosis of the intracranial segment of the vertebral artery. Clinically， for patients with the aforementioned characteristics， more imaging screening and risk assessment of the intracranial segment of the vertebral artery should be enhanced.