Lake Douglas E, Richman Joshua S, Griffin M Pamela, Moorman J Randall
Department of Internal Medicine, University of Virginia, Charlottesville, Virginia 22908, USA.
Am J Physiol Regul Integr Comp Physiol. 2002 Sep;283(3):R789-97. doi: 10.1152/ajpregu.00069.2002.
Abnormal heart rate characteristics of reduced variability and transient decelerations are present early in the course of neonatal sepsis. To investigate the dynamics, we calculated sample entropy, a similar but less biased measure than the popular approximate entropy. Both calculate the probability that epochs of window length m that are similar within a tolerance r remain similar at the next point. We studied 89 consecutive admissions to a tertiary care neonatal intensive care unit, among whom there were 21 episodes of sepsis, and we performed numerical simulations. We addressed the fundamental issues of optimal selection of m and r and the impact of missing data. The major findings are that entropy falls before clinical signs of neonatal sepsis and that missing points are well tolerated. The major mechanism, surprisingly, is unrelated to the regularity of the data: entropy estimates inevitably fall in any record with spikes. We propose more informed selection of parameters and reexamination of studies where approximate entropy was interpreted solely as a regularity measure.
新生儿败血症病程早期会出现心率变异性降低和短暂减速等异常心率特征。为了研究其动态变化，我们计算了样本熵，这是一种比常用的近似熵更相似但偏差更小的测量方法。两者都计算窗口长度为m的时段在容差r内相似且在下一个点仍保持相似的概率。我们研究了一家三级医疗新生儿重症监护病房连续收治的89例患者，其中有21例败血症发作，并进行了数值模拟。我们探讨了m和r的最佳选择以及缺失数据的影响等基本问题。主要发现是，熵在新生儿败血症临床体征出现之前就会下降，而且缺失点具有良好的耐受性。令人惊讶的是，主要机制与数据的规律性无关：在任何有尖峰的记录中，熵估计值都会不可避免地下降。我们建议更明智地选择参数，并重新审视那些仅将近似熵解释为规律性度量的研究。
