Sarà Marco, Sebastiano Fabio, Sacco Simona, Pistoia Francesca, Onorati Paolo, Albertini Giorgio, Carolei Antonio
Istituto San Raffaele - Tosinvest Sanità, Post-Coma Intensive and Rehabilitation Care Unit, Cassino, Italy.
Brain Inj. 2008 Jan;22(1):33-7. doi: 10.1080/02699050701810670.
This study evaluated the hypothesis that neural networks derangement in patients with a vegetative state (VS) may cause an alteration of heart rate (HR) non-linear pattern.
Fifteen consecutive patients with a persistent VS and 15 matched healthy control subjects were included in the study. A 6-hour continuous electrocardiographic recording was used for the time series analysis measuring the occurrence time of the intervals between consecutive normal sinus heart beats (RR' intervals). Parameters evaluating linear and non-linear HR variability were studied. Approximate Entropy (ApEn), a non-linear parameter that quantifies the unpredictability of fluctuations in an instantaneous HR time series, was calculated from the average values of time series with fixed input variables.
All linear parameters, with the only exception being the percentage of RR' intervals that were by at least 50 ms different from the previous interval (0.56, SD = 1.31 vs 10.35, SD = 12.58; p = 0.005) were similar in patients and in healthy control subjects. Mean ApEn values (0.68, SD = 0.24 vs 1.10, SD = 0.16; p = 0.0001) were lower in patients than in healthy control subjects.
The findings support the hypothesis that derangement of neural networks may cause a reduction of non-linear behaviour in HR such as ApEn.
本研究评估了如下假设,即植物状态(VS)患者的神经网络紊乱可能导致心率(HR)非线性模式的改变。
本研究纳入了15例持续性VS患者和15例匹配的健康对照者。使用6小时连续心电图记录进行时间序列分析,测量连续正常窦性心搏间期(RR'间期)的发生时间。研究了评估线性和非线性HR变异性的参数。近似熵(ApEn)是一种非线性参数,用于量化瞬时HR时间序列波动的不可预测性,它是根据具有固定输入变量的时间序列平均值计算得出的。
除RR'间期与前一个间期至少相差50毫秒的百分比外(0.56,标准差=1.31 vs 10.35,标准差=12.58;p=0.005),患者和健康对照者的所有线性参数均相似。患者的平均ApEn值(0.68,标准差=0.24 vs 1.10,标准差=0.16;p=0.0001)低于健康对照者。
这些发现支持了神经网络紊乱可能导致HR非线性行为(如ApEn)降低的假设。