Università degli Studi di Milano, Dipartimento di Tecnologie per la Salute, Istituto Ortopedico Galeazzi, Laboratorio di Modellistica di Sistemi Complessi, Via R. Galeazzi 4, Milan, Italy.
Am J Physiol Heart Circ Physiol. 2010 May;298(5):H1406-14. doi: 10.1152/ajpheart.01206.2009. Epub 2010 Feb 12.
Open-loop linear parametric models were exploited to describe ventricular repolarization duration (VRD) variability during graded head-up tilt. Surface ECG and thoracic movements were recorded in 15 healthy humans (age: 24-54 yr, median: 28 yr; 6 women and 9 men). Tilt table inclinations ranged from 15 to 90 degrees and were varied in steps of 15 degrees . All subjects underwent recordings at every step in random order. Heart period was assessed as the time difference between two consecutive R-wave peaks (RR) and the respiratory signal (R) as the sampling of the thoracic movement signal at the R-wave peaks. VRD was measured automatically as the temporal difference between the R-wave peak and T-wave apex (RT(a)) or T-wave end (RT(e)). The best model decomposed RT variability as due to RR changes (RR-related RT variability) to direct respiratory-related inputs (R-related RT variability) and to unknown rhythmical sources unrelated to RR changes and R (RR-R-unrelated RT variability). Using this model, RT(e) variability was found to be less predictable than RT(a) variability and composed of a smaller fraction of RR-related RT variability and a larger fraction of RR-R-unrelated RT variability. Predictability progressively decreased with tilt table angles, suggesting increased complexity of RT regulation. RT variance progressively increased with tilt table inclination. This increase was characterized by a gradual rise of the amount of RR-R-unrelated RT variability, whereas the amount of RR-related RT variability remained unchanged. These results suggest that the amount of RT variability, complexity of RT dynamics, and amount of RR-R-unrelated RT variability increase with the magnitude of the sympathetic drive directly related to tilt table inclination. We propose the utilization of the amount of RR-R-unrelated RT variability instead of overall RT variability as an indirect measure of autonomic regulation directed to ventricles.
开环线性参数模型被用于描述在逐渐头高位倾斜期间心室复极持续时间(VRD)的变化。在 15 名健康个体(年龄:24-54 岁,中位数:28 岁;6 名女性和 9 名男性)中记录了体表心电图和胸部运动。倾斜台的倾斜角度范围从 15 度到 90 度,以 15 度的步长变化。所有受试者随机在每个步骤进行记录。心动周期被评估为两个连续 R 波峰(RR)之间的时间差,呼吸信号(R)为 R 波峰处胸部运动信号的采样。VRD 被自动测量为 R 波峰和 T 波顶点(RT(a))或 T 波终点(RT(e))之间的时间差。最佳模型将 RT 变化分解为 RR 变化引起的变化(RR 相关 RT 变化)、直接呼吸相关输入(R 相关 RT 变化)和与 RR 变化和 R 无关的未知节律性源(RR-R 无关 RT 变化)。使用该模型,发现 RT(e)变化的可预测性低于 RT(a)变化,并且由较小比例的 RR 相关 RT 变化和较大比例的 RR-R 无关 RT 变化组成。随着倾斜台角度的增加,可预测性逐渐降低,表明 RT 调节的复杂性增加。随着倾斜台倾斜度的增加,RT 方差逐渐增加。这种增加的特征是 RR-R 无关 RT 变化量逐渐增加,而 RR 相关 RT 变化量保持不变。这些结果表明,随着与倾斜台倾斜度直接相关的交感神经驱动的大小增加,RT 变化量、RT 动力学的复杂性和 RR-R 无关 RT 变化量增加。我们建议使用 RR-R 无关 RT 变化量而不是整体 RT 变化量作为间接测量心室自主调节的指标。