Wu Lingheng, Jin Lin, Li Xinyi, Zhang Mengjiao, Chen Jianxiong, Tang Xiaobo, Du Lianfang, Wang Xifu, Li Zhaojun, Luo Xianghong
Department of Ultrasound, Mindong Hospital Affiliated to Fujian Medical University, Ningde, China.
Department of Ultrasound, Shanghai General Hospital of Nanjing Medical University, Shanghai, China.
Front Med (Lausanne). 2025 Aug 29;12:1594570. doi: 10.3389/fmed.2025.1594570. eCollection 2025.
This study aimed to investigate the correlation between the severity of pulmonary infection and arterial stiffness pulse in coronavirus disease 2019 (COVID-19) patients using artificial intelligence (AI) quantitative analysis.
A total of 100 COVID-19 patients (with a mean age of 76 years) were enrolled in this study and were stratified into three groups based on the severity of their condition: mild, moderate, and severe. An AI imaging diagnostic system was used for automatic identification and quantitative analysis of infected lesions. Arterial stiffness was evaluated using the arterial velocity pulse index (AVI). Multiple linear regression analyses were performed to investigate the independent associations between the AVI, inflammatory markers, and radiographic parameters. Hazard ratios and Kaplan-Meier curves were produced to assess the association between arterial stiffness and radiographic parameters in relation to the composite outcome of all-cause mortality.
The AVI was elevated in the moderate and severe groups compared to the mild COVID-19 group ( < 0.001). Multiple linear regression analyses showed that the AVI was associated with the highest percentage of lobe infection ( = 0.813, 95%CI, 0.056-0.394, = 0.011). Multivariable Cox regression showed that an AVI ≥ 33 was associated with all-cause mortality {hazard ratio, 16.201 [95% confidence interval (CI), 1.601, 163.987]}.
As the severity of pneumonia infection increased in COVID-19 patients, vascular endothelial function was impaired, leading to increased arterial stiffness. The AVI was associated with the highest percentage of lobe infection, and the severity of pneumonia was identified as an independent risk factor for increased arterial stiffness. Worsening arterial stiffness poses an increased risk of death in COVID-19 patients.
本研究旨在通过人工智能（AI）定量分析，探讨2019冠状病毒病（COVID-19）患者肺部感染严重程度与动脉僵硬度脉搏之间的相关性。
本研究共纳入100例COVID-19患者（平均年龄76岁），并根据病情严重程度分为三组：轻度、中度和重度。使用AI成像诊断系统对感染病灶进行自动识别和定量分析。采用动脉速度脉搏指数（AVI）评估动脉僵硬度。进行多元线性回归分析，以研究AVI、炎症标志物和影像学参数之间的独立关联。生成风险比和Kaplan-Meier曲线，以评估动脉僵硬度与影像学参数之间与全因死亡率复合结局的关联。
与轻度COVID-19组相比，中度和重度组的AVI升高（<0.001）。多元线性回归分析显示，AVI与肺叶感染百分比最高相关（=0.813，95%CI，0.056-0.394，=0.011）。多变量Cox回归显示，AVI≥33与全因死亡率相关{风险比，16.201[95%置信区间（CI），1.601，163.987]}。
随着COVID-19患者肺部感染严重程度增加，血管内皮功能受损，导致动脉僵硬度增加。AVI与肺叶感染百分比最高相关，肺炎严重程度被确定为动脉僵硬度增加的独立危险因素。动脉僵硬度恶化使COVID-19患者死亡风险增加。
