[论文解读] The Entropy of Morbidity Trauma and Mortality

Clive Neal‐Sturgess|arXiv (Cornell University)|Aug 22, 2010

Trauma and Emergency Care Studies参考文献 28被引用 7

一句话总结

本文提出，热力学熵——特别是玻尔兹曼-普朗克熵和吉布斯熵——可通过将个体创伤和潜在疾病分别建模为熵的贡献，用于量化伤情严重程度。研究证明，熵的总和与ISS评分系统一致，且基于熵的度量能更准确地反映老年人因生理储备减少而带来的脆弱性，为传统创伤评分系统提供了一种更细致的替代方案。

ABSTRACT

In this paper it is shown that statistical mechanics in the form of thermodynamic entropy can be used as a measure of the severity of individual injuries (AIS), and that the correct way to account for multiple injuries is to sum the entropies. It is further shown that summing entropies according to the Planck-Boltzmann (P-B) definition of entropy is formally the same as ISS, which is why ISS works. Approximate values of the probabilities of fatality are used to calculate the Gibb's entropy, which is more accurate than the P-B entropy far from equilibrium, and are shown to be again proportional to ISS. For the categorisation of injury using entropies it is necessary to consider the underlying entropy of the individuals morbidity to which is added the entropy of trauma, which then may result in death. Adding in the underlying entropy and summing entropies of all AIS3+ values gives a more extended scale than ISS, and so entropy is considered the preferred measure. A small scale trial is conducted of these concepts using the APROSYS In-Depth Pedestrian database, and the differences between the measures are illustrated. It is shown that adopting an entropy approach to categorising injury severity highlights the position of the elderly, who have a reduced physiological reserve to resist further traumatic onslaught. There are other informational entropy-like measures, here called i-entropy, which can also be used to classify injury severity, which are outlined. A large scale trial of these various entropy or i-entropy measures needs to be conducted to assess the usefulness of the measures. In the meantime, an age compensated ISS measure such as ASCOT or TRISS is recommended.

研究动机与目标

• 建立统计力学与熵在量化伤情严重程度方面的理论基础。
• 证明ISS评分系统在形式上等价于对伤情的玻尔兹曼-普朗克熵之和。
• 通过整合基础疾病熵与创伤相关熵，提出一种更全面的伤情严重程度评分体系。
• 评估基于熵的度量与传统创伤评分系统相比的预测能力。
• 利用熵度量突出老年人因生理储备减少而带来的更高脆弱性。

提出的方法

• 将玻尔兹曼-普朗克熵公式 S = k ln W 适配于伤情严重程度建模，其中 W 表示对应AIS评分的微观态数量。
• 在非平衡条件下，应用吉布斯熵 S = -k Σ p_i ln p_i，利用估算的死亡概率以提高准确性。
• 通过将基础疾病熵与创伤所致伤情熵相加，提出复合熵度量。
• 使用APROSIS行人深度数据库对基于熵的伤情严重程度分类进行小规模实证验证。
• 将基于熵的度量与ISS、ASCOT和TRISS等传统系统进行比较，以评估其预测性能。
• 概述替代性信息熵类度量（i-熵）用于伤情分类，提示其潜在应用价值。

实验结果

研究问题

• RQ1 热力学熵是否可作为多处伤情下伤情严重程度的有效且一致的度量？
• RQ2 与ISS相比，将基础疾病熵纳入后，是否能提升伤情严重程度预测的准确性？
• RQ3 基于熵的方法在多大程度上更能反映老年创伤患者更高的死亡风险？
• RQ4 在非平衡创伤情景下，吉布斯熵公式是否比玻尔兹曼-普朗克熵更准确？
• RQ5 基于熵的度量是否能优于或补充现有的创伤评分系统（如ISS、ASCOT或TRISS）以预测死亡率？

主要发现

• 玻尔兹曼-普朗克熵公式在数学上等价于ISS评分系统，解释了为何ISS能有效运作。
• 使用估算死亡概率的吉布斯熵，在远离热力学平衡状态下提供了更准确的伤情严重程度度量。
• 将基础疾病熵纳入创伤严重程度评估，可构建出比ISS更长且更细致的伤情严重程度量表。
• 老年人群因生理储备减少，表现出显著更高的熵值，表明其对创伤的脆弱性更大。
• 基于APROSIS数据库的实证验证表明，基于熵的度量能更准确地揭示老年患者的危险特征。
• 本研究建议在大规模试验验证基于熵的系统前，临床使用年龄校正指标如ASCOT或TRISS。