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关于使用临床值的群论方法的进一步建议。

Further suggestions on the group-theoretical approach using clinical values.

作者信息

Sawamura Jitsuki, Morishita Shigeru, Ishigooka Jun

机构信息

Department of Psychiatry, Tokyo Women's Medical University, Tokyo, Japan.

出版信息

Theor Biol Med Model. 2012 Dec 19;9:54. doi: 10.1186/1742-4682-9-54.

Abstract

BACKGROUND

In a previous report, we suggested a prototypal model to describe patient states in a graded vector-like format based on the modulo groups via the psychiatric rating scale. In this article, using other simple examples, we provide additional suggestions to clarify how other clinical data can be treated practically in line with our proposed model.

METHODS

As illustrations of the wider applicability, we treat four cases commensurate with modulo arithmetic: 1) prescription doses of three medicines (lithium carbonate, mirtazapine, and nitrazepam), 2) changes in laboratory data (blood concentrations of lithium carbonate, white blood cells, percutaneous oxygen saturation and systolic blood pressure), 3) the tumor node metastasis (TNM) classification of malignant tumors applied for esophageal tumors, and 4) the coding schemes of the International Classification of Diseases (ICD) for selected diseases or laboratory data. For each case, we present simple examples in the form of product of states to illustrate these results.

RESULTS

  1. Medications and their changes can be represented as elements of a modulo group; e.g., group S = {Sj | Sj ε Z(13)×Z(4)×Z(3)} can represent the set of all possible prescription combinations of three specified medicines. Likewise, 2) clinical values can also be expressed as a modulo group; e.g., group T = {Tj | Tj ε Z(600)×Z(50000)×Z(100)×Z(300)} representing the set of all possible data based on any number of clinical values and their differences. Also, 3) the TNM classification for malignant tumors can be treated within a single modulo group C = {Cj | Cj ε Z(8)×Z(4)×Z(2)×Z(2)}, the set of all composable disease states graded in terms of tumor expansion. Finally, 4) ICD coding schemes provide several examples treatable as a modulo group D = {Dj | Dj ε Z(7)×Z(7)× …×Z(7) (an n-fold product)}, constituting the set of all possible severities of diseases states and laboratory data within provided tuples.

CONCLUSIONS

Despite the limited scope of our methodology, there are grounds where other clinical quantities (prescription of medicine, laboratory data, TNM classification of malignant tumors, and ICD coding schemes) can be also treatable with the same group-theory approach as was suggested for psychiatric disease states in our previous report.

摘要

背景

在之前的一份报告中,我们提出了一个原型模型,通过精神科评定量表,以类似分级向量的形式基于模群来描述患者状态。在本文中,我们通过其他简单示例,提供更多建议以阐明如何根据我们提出的模型实际处理其他临床数据。

方法

为说明更广泛的适用性,我们处理四个与模运算相关的案例:1)三种药物(碳酸锂、米氮平、硝西泮)的处方剂量;2)实验室数据的变化(碳酸锂血药浓度、白细胞、经皮血氧饱和度和收缩压);3)应用于食管肿瘤的恶性肿瘤的肿瘤淋巴结转移(TNM)分类;4)选定疾病或实验室数据的国际疾病分类(ICD)编码方案。对于每个案例,我们以状态乘积的形式给出简单示例来说明这些结果。

结果

1)药物及其变化可以表示为模群的元素;例如,集合S = {Sj | Sj ε Z(13)×Z(4)×Z(3)}可以表示三种特定药物所有可能的处方组合集。同样,2)临床值也可以表示为模群;例如,集合T = {Tj | Tj ε Z(600)×Z(50000)×Z(100)×Z(300)}表示基于任意数量临床值及其差异的所有可能数据的集合。此外,3)恶性肿瘤的TNM分类可以在单个模群C = {Cj | Cj ε Z(8)×Z(4)×Z(2)×Z(2)}内处理,该集合是根据肿瘤扩展分级的所有可组合疾病状态的集合。最后,4)ICD编码方案提供了几个可作为模群D = {Dj | Dj ε Z(7)×Z(7)×…×Z(7)(n重乘积)}处理的示例,构成了给定元组内疾病状态和实验室数据所有可能严重程度的集合。

结论

尽管我们方法的范围有限,但有理由认为其他临床量(药物处方、实验室数据、恶性肿瘤的TNM分类和ICD编码方案)也可以用与我们之前报告中针对精神疾病状态所建议的相同群论方法来处理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae0c/3586959/27ffea7bd2aa/1742-4682-9-54-1.jpg

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