Health Information and Decision Sciences Department, Faculty of Medicine, University of Porto, Porto, Portugal; Instituto de Telecomunicações, Porto, Portugal; Centre for Research in Health Technologies and Information Systems - CINTESIS, Porto, Portugal.
J Eval Clin Pract. 2013 Dec;19(6):1101-6. doi: 10.1111/jep.12068. Epub 2013 Jun 27.
RATIONALE, AIMS AND OBJECTIVES: Traditional complexity measures are used to capture the amount of structured information present in a certain phenomenon. Several approaches developed to facilitate the characterization of complexity have been described in the related literature. Fetal heart rate (FHR) monitoring has been used and improved during the last decades. The importance of these studies lies on an attempt to predict the fetus outcome, but complexity measures are not yet established in clinical practice. In this study, we have focused on two conceptually different measures: Shannon entropy, a probabilistic approach, and Kolmogorov complexity, an algorithmic approach. The main aim of the current investigation was to show that approximation to Kolmogorov complexity through different compressors, although applied to a lesser extent, may be as useful as Shannon entropy calculated by approximation through different entropies, which has been successfully applied to different scientific areas.
To illustrate the applicability of both approaches, two entropy measures, approximate and sample entropy, and two compressors, paq8l and bzip2, were considered. These indices were applied to FHR tracings pertaining to a dataset composed of 48 delivered fetuses with umbilical artery blood (UAB) pH in the normal range (pH ≥ 7.20), 10 delivered mildly acidemic fetuses and 10 moderate-to-severe acidemic fetuses. The complexity indices were computed on the initial and final segments of the last hour of labour, considering 5- and 10-minute segments.
In our sample set, both entropies and compressors were successfully utilized to distinguish fetuses at risk of hypoxia from healthy ones. Fetuses with lower UAB pH presented significantly lower entropy and compression indices, more markedly in the final segments.
The combination of these conceptually different measures appeared to present an improved approach in the characterization of different pathophysiological states, reinforcing the theory that entropies and compressors measure different complexity features. In view of these findings, we recommend a combination of the two approaches.
传统的复杂性度量方法用于捕捉特定现象中存在的结构化信息量。相关文献中已经描述了几种旨在促进复杂性特征描述的方法。在过去的几十年中，胎儿心率（FHR）监测得到了应用和改进。这些研究的重要性在于试图预测胎儿的结局，但复杂性度量在临床实践中尚未确立。在这项研究中，我们集中研究了两种概念上不同的度量方法：香农熵，一种概率方法，和柯尔莫哥洛夫复杂度，一种算法方法。本研究的主要目的是表明，通过不同的压缩器来逼近柯尔莫哥洛夫复杂度，尽管应用程度较低，但可能与通过不同的熵来近似计算的香农熵一样有用，这种方法已成功应用于不同的科学领域。
为了说明这两种方法的适用性，我们考虑了两种熵度量，近似熵和样本熵，以及两种压缩器，paq8l 和 bzip2。这些指数应用于 48 例脐带血（UAB）pH 值在正常范围内（pH≥7.20）的分娩胎儿、10 例轻度酸中毒胎儿和 10 例中重度酸中毒胎儿的 FHR 描记。在分娩最后 1 小时的初始和最终段，考虑到 5 分钟和 10 分钟的片段，计算复杂性指数。
在我们的样本集中，熵和压缩器都成功地用于区分有缺氧风险的胎儿和健康胎儿。UAB pH 值较低的胎儿呈现出显著较低的熵和压缩指数，在最后段更为明显。
这些概念上不同的方法的组合似乎提供了一种改进的方法来描述不同的病理生理状态，这加强了熵和压缩器测量不同复杂性特征的理论。鉴于这些发现，我们建议结合这两种方法。
