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短期多尺度复杂度分析心血管变异性可改善冠状动脉旁路移植术后低心输出量综合征的风险分层。

Short-term multiscale complexity analysis of cardiovascular variability improves low cardiac output syndrome risk stratification after coronary artery bypass grafting.

机构信息

Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy.

出版信息

Physiol Meas. 2019 Apr 26;40(4):044001. doi: 10.1088/1361-6579/ab12f0.

Abstract

BACKGROUND

Low cardiac output syndrome (LCOS) is a myocardial dysfunction leading to systemic hypoperfusion, favored by particular conditions of the autonomic nervous system. LCOS is one of the adverse events that might occur after cardiac surgery.

OBJECTIVE

The aim is to test the hypothesis that short-term multiscale complexity (MSC) analysis of heart period (HP) and systolic arterial pressure (SAP) variability series in the frequency bands typical of cardiovascular control could be fruitfully exploited in identifying subjects at risk of developing LCOS after coronary artery bypass graft (CABG).

APPROACH

HP and SAP beat-to-beat series were derived from electrocardiogram (ECG) and invasive arterial pressure (AP) signal acquired in 128 patients scheduled for CABG before (PRE) and after (POST) the induction of general anesthesia with propofol and remifentanil. Subjects were labeled as LCOS (n  =  14) and noLCOS (n  =  114) according to the LCOS development. MSC markers were calculated as the complement to 1 of the modulus of the average position of the poles dropping in the low-frequency (LF, 0.04-0.15 Hz) and high-frequency (HF, 0.15-0.5 Hz) bands as derived from the autoregressive model of HP and SAP series. Traditional time and frequency domain indexes were also calculated.

MAIN RESULTS

Traditional parameters were able to assess the depression of the cardiovascular regulation induced by general anesthesia, but showed weak performances in differentiating LCOS and noLCOS groups. Conversely, HP complexity in LF band and SAP complexity in HF band assessed during POST remained associated with LCOS even after entering a multivariate logistic regression model adjusted for clinical and demographic factors.

SIGNIFICANCE

The MSC approach can be fruitfully applied to improve risk stratification for LCOS after CABG likely because MSC markers describe the dysfunction of the sympathetic control and the impairment of the mechanical properties of the heart in the LCOS group.

摘要

背景

低心输出综合征(LCOS)是一种导致全身低灌注的心肌功能障碍,其发生与自主神经系统的特定条件有关。LCOS 是心脏手术后可能发生的不良事件之一。

目的

本研究旨在验证假设,即通过对心率(HP)和收缩压(SAP)变异性系列的多尺度复杂度(MSC)进行短期分析,可以充分利用心血管控制的典型频带,来识别发生冠状动脉旁路移植术(CABG)后发生 LCOS 的风险。

方法

从接受丙泊酚和瑞芬太尼全身麻醉诱导前后(PRE 和 POST)的 128 例行 CABG 的患者的心电图(ECG)和有创动脉压(AP)信号中提取 HP 和 SAP 逐拍序列。根据 LCOS 的发展情况,将患者标记为 LCOS(n=14)和非 LCOS(n=114)。MSC 标志物计算为 HP 和 SAP 序列自回归模型中低频(LF,0.04-0.15 Hz)和高频(HF,0.15-0.5 Hz)带中极点平均位置的模的倒数的补数。还计算了传统的时频域指标。

主要结果

传统参数能够评估全身麻醉引起的心血管调节抑制,但在区分 LCOS 和非 LCOS 组方面表现不佳。相反,POST 时 HP 的 LF 带复杂度和 SAP 的 HF 带复杂度与 LCOS 相关,即使在进入调整了临床和人口统计学因素的多变量逻辑回归模型后,仍具有相关性。

意义

MSC 方法可成功应用于改善 CABG 后 LCOS 的风险分层,这可能是因为 MSC 标志物描述了 LCOS 组中交感神经控制的功能障碍和心脏机械性能的损害。

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