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个体化脉搏波传播模型识别血液透析患者的心血管风险特征。

Patient-specific pulse wave propagation model identifies cardiovascular risk characteristics in hemodialysis patients.

机构信息

Department for Mathematical Modeling of Physiological Processes, Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Warsaw, Poland.

Department of Anesthesiology and Intensive Therapy, Medical University of Lublin, Lublin, Poland.

出版信息

PLoS Comput Biol. 2018 Sep 14;14(9):e1006417. doi: 10.1371/journal.pcbi.1006417. eCollection 2018 Sep.

Abstract

Risk of cardiovascular associated death in dialysis patients is the highest among all other co-morbidities. Improving the identification of patients with the highest cardiovascular risk to design an adequate treatment is, therefore, of utmost importance. There are several non-invasive cardiovascular state biomarkers based on the pulse (pressure) wave propagation properties, but their major determinants are not fully understood. In the current study we aimed to provide a framework to precisely dissect the information available in non-invasively recorded pulse wave in hemodialysis patients. Radial pressure wave profiles were recorded before, during and after two independent hemodialysis sessions in 35 anuric prevalent hemodialysis patients and once in a group of 32 healthy volunteers. Each recording was used to estimate six subject-specific parameters of pulse wave propagation model. Pressure profiles were also analyzed using SphygmoCor software (AtCor Medical, Australia) to derive values of already established biomarkers, i.e. augmentation index and sub-endocardial viability ratio (SEVR). Data preprocessing using propensity score matching allowed to compare hemodialysis and healthy groups. Augmentation index remained on average stable at 142 ± 28% during dialysis and had similar values in both considered groups. SEVR, whose pre-dialytic value was on average lower by 12% compared to healthy participants, was improved by hemodialysis, with post-dialytic values indistinguishable from those in healthy population (p-value > 0.2). The model, however, identified that the patients on hemodialysis had significantly increased stiffness of both large and small arteries compared to healthy counterparts (> 60% before dialysis with p-value < 0.05 or borderline) and that it was only transiently decreased during hemodialysis session. Additionally, correlation-based clustering revealed that augmentation index reflects the shape of heart ejection profile and SEVR is associated with stiffness of larger arteries. Patient-specific pulse wave propagation modeling coupled with radial pressure profile recording correctly identified increased arterial stiffness in hemodialysis patients, while regular pulse wave analysis based biomarkers failed to show significant differences. Further model testing in larger populations and investigating other biomarkers are needed to confirm these findings.

摘要

在所有合并症中,透析患者的心血管相关死亡风险最高。因此,提高对具有最高心血管风险患者的识别能力,以制定适当的治疗方案至关重要。有几种基于脉搏(压力)波传播特性的无创心血管状态生物标志物,但它们的主要决定因素尚未完全了解。在本研究中,我们旨在为精确剖析透析患者无创记录的脉搏波中可用信息提供一个框架。在 35 名无尿期常规透析患者的两次独立透析期间和之后,以及在 32 名健康志愿者的一次记录中,记录了桡动脉压力波轮廓。每次记录都用于估计脉搏波传播模型的六个个体特定参数。还使用 SphygmoCor 软件(澳大利亚 AtCor Medical)分析压力曲线,以得出已建立的生物标志物的数值,即增强指数和心内膜下活力比(SEVR)。使用倾向评分匹配进行的数据预处理允许比较透析组和健康组。增强指数在透析过程中平均稳定在 142±28%,并且在两个考虑的组中具有相似的值。SEVR 的预透析值平均比健康参与者低 12%,通过血液透析得到改善,透析后的值与健康人群无法区分(p 值>0.2)。然而,该模型确定,与健康对照组相比,血液透析患者的大、小动脉的僵硬程度显著增加(透析前增加超过 60%,p 值<0.05 或边缘),并且仅在血液透析过程中短暂降低。此外,基于相关性的聚类表明,增强指数反映了心脏射血轮廓的形状,SEVR 与较大动脉的僵硬程度相关。患者特定的脉搏波传播建模与桡动脉压力曲线记录相结合,可以正确识别血液透析患者的动脉僵硬程度,而基于常规脉搏波分析的生物标志物未能显示出显著差异。需要在更大的人群中进一步测试模型并研究其他生物标志物,以确认这些发现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92d9/6157900/e3caca642dd7/pcbi.1006417.g001.jpg

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