Henriques Teresa S, Costa Madalena D, Mathur Pooja, Mathur Priyam, Davis Roger B, Mittleman Murray A, Khabbaz Kamal R, Goldberger Ary L, Subramaniam Balachundhar
Center for Anesthesia Research Excellence (CARE), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, 02215, USA.
Margret and H.A. Rey Institute of Nonlinear Dynamics in Physiology and Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
J Clin Monit Comput. 2019 Feb;33(1):31-38. doi: 10.1007/s10877-018-0133-4. Epub 2018 Mar 21.
Complexity measures are intended to assess the cardiovascular system's capacity to respond to stressors. We sought to determine if decreased BP complexity is associated with increased estimated risk as obtained from two standard instruments: the Society of Thoracic Surgeons' (STS) Risk of Mortality and Morbidity Index and the European System for Cardiac Operative Risk Evaluation Score (EuroSCORE II). In this observational cohort study, preoperative systolic, diastolic, mean (MAP) and pulse pressure (PP) time series were derived in 147 patients undergoing cardiac surgery. The complexity of the fluctuations of these four variables was quantified using multiscale entropy (MSE) analysis. In addition, the traditional time series measures, mean and standard deviation (SD) were also computed. The relationships between time series measures and the risk indices (after logarithmic transformation) were then assessed using nonparametric (Spearman correlation, r) and linear regression methods. A one standard deviation change in the complexity of systolic, diastolic and MAP time series was negatively associated (p < 0.05) with the STS and EuroSCORE indices in both unadjusted (21-34%) and models adjusted for age, gender and SD of the BP time series (15-31%). The mean and SD of BP time series were not significantly associated with the risk index except for a positive association with the SD of the diastolic BP. Lower preoperative BP complexity was associated with a higher estimated risk of adverse cardiovascular outcomes and may provide a novel approach to assessing cardiovascular risk. Future studies are needed to determine whether dynamical risk indices can improve current risk prediction tools.
复杂性度量旨在评估心血管系统对应激源的反应能力。我们试图确定血压复杂性降低是否与通过两种标准工具得出的估计风险增加相关:胸外科医师协会(STS)的死亡率和发病率风险指数以及欧洲心脏手术风险评估系统评分(EuroSCORE II)。在这项观察性队列研究中,对147例接受心脏手术的患者术前的收缩压、舒张压、平均动脉压(MAP)和脉压(PP)时间序列进行了分析。使用多尺度熵(MSE)分析对这四个变量波动的复杂性进行了量化。此外,还计算了传统的时间序列度量,即均值和标准差(SD)。然后使用非参数方法(Spearman相关性,r)和线性回归方法评估时间序列度量与风险指数(对数转换后)之间的关系。在未调整模型(21 - 34%)以及针对年龄、性别和血压时间序列标准差进行调整的模型(15 - 31%)中,收缩压、舒张压和MAP时间序列复杂性的一个标准差变化与STS和EuroSCORE指数呈负相关(p < 0.05)。血压时间序列的均值和标准差与风险指数无显著关联,除了舒张压标准差呈正相关。术前较低的血压复杂性与较高的不良心血管结局估计风险相关,可能为评估心血管风险提供一种新方法。需要进一步的研究来确定动态风险指数是否能改进当前的风险预测工具。