Department of Medicine, MacKay Medical College, No. 46, Sec. 3, Jhong-Jheng Rd., San-Jhih District, New Taipei City, Taiwan.
Institute of Biomedical Sciences, MacKay Medical College, New Taipei City, Taiwan.
Sci Rep. 2024 May 27;14(1):12032. doi: 10.1038/s41598-024-62866-7.
Hemodynamic parameters have been correlated with stroke, hypertension, and arterial stenosis. While only a few small studies have examined the link between hemodynamics and diabetes mellitus (DM). This case-control study enrolled 417 DM patients and 3475 non-DM controls from a community-based cohort. Peak systolic velocity (PSV), end-diastolic velocity (EDV), blood flow velocity (MFV), pulsatility index (PI), and the resistance index (RI) of the common carotid arteries were measured by color Doppler ultrasonography. Generalized linear regression analyses showed that as compared to the non-DM controls, the age-sex-adjusted means of PSV, EDV, and MFV were - 3.28 cm/sec, - 1.94 cm/sec, and - 2.38 cm/sec, respectively, lower and the age-sex-adjusted means of RI and PI were 0.013 and 0.0061, respectively, higher for the DM cases (all p-values < 0.0005). As compared to the lowest quartiles, the multivariable-adjusted ORs of DM for the highest quartiles of PSV, EDV, MFV, RI, and PI were 0.59 (95% confidence interval [CI] 0.41-0.83), 0.45 (95% CI 0.31-0.66), 0.53 (95% CI 0.37-0.77), 1.61 (95% CI 1.15-2.25), and 1.58 (95% CI 1.12-2.23), respectively. More importantly, the additions of EDV significantly improved the predictabilities of the regression models on DM. As compared to the model contained conventional CVD risk factors alone, the area under the receiver operating curve (AUROC) increased by 1.00% (95% CI 0.29-1.73%; p = 0.0059) and 0.80% (95% CI 0.15-1.46%; p = 0.017) for models that added EDV in continuous and quartile scales, respectively. Additionally, the additions of PSV and MFV also significantly improved the predictabilities of the regression models (all 0.01 < p-value < 0.05). This study reveals a significant correlation between DM and altered hemodynamic parameters. Understanding this relationship could help identify individuals at higher risk of DM and facilitate targeted preventive strategies to reduce cardiovascular complications in DM patients.
血流动力学参数与中风、高血压和动脉狭窄有关。虽然只有少数小型研究检查了血流动力学与糖尿病(DM)之间的联系。这项病例对照研究纳入了来自社区队列的 417 名 DM 患者和 3475 名非 DM 对照者。采用彩色多普勒超声测量颈总动脉的收缩期峰值速度(PSV)、舒张末期速度(EDV)、血流速度(MFV)、搏动指数(PI)和阻力指数(RI)。广义线性回归分析显示,与非 DM 对照组相比,DM 病例的 PSV、EDV 和 MFV 的年龄性别调整平均值分别低-3.28 cm/sec、-1.94 cm/sec 和-2.38 cm/sec,而 RI 和 PI 的年龄性别调整平均值分别高 0.013 和 0.0061(所有 p 值均<0.0005)。与最低四分位数相比,PSV、EDV、MFV、RI 和 PI 的四分位数最高的 DM 的多变量调整比值比(OR)分别为 0.59(95%置信区间[CI]为 0.41-0.83)、0.45(95%CI 为 0.31-0.66)、0.53(95%CI 为 0.37-0.77)、1.61(95%CI 为 1.15-2.25)和 1.58(95%CI 为 1.12-2.23)。更重要的是,EDV 的加入显着提高了回归模型对 DM 的预测能力。与仅包含传统 CVD 危险因素的模型相比,接受者操作特征曲线(AUROC)下面积增加了 1.00%(95%CI 为 0.29-1.73%;p=0.0059)和 0.80%(95%CI 为 0.15-1.46%;p=0.017),分别用于以连续和四分位数为单位添加 EDV 的模型。此外,PSV 和 MFV 的加入也显着提高了回归模型的预测能力(所有 p 值均<0.05)。这项研究揭示了 DM 与改变的血流动力学参数之间存在显着相关性。了解这种关系可以帮助确定更高风险的 DM 个体,并促进针对 DM 患者心血管并发症的有针对性的预防策略。