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Strong Relationships in Acid-Base Chemistry – Modeling Protons Based on Predictable Concentrations of Strong Ions Total Weak Acid Concentrations and pCO2

机译:酸碱化学中的强关系–基于可预测的强离子浓度总弱酸浓度和pCO2建模质子

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摘要

Understanding acid-base regulation is often reduced to pigeonholing clinical states into categories of disorders based on arterial blood sampling. An earlier ambition to quantitatively explain disorders by measuring production and elimination of acid has not become standard clinical practice. Seeking back to classical physical chemistry we propose that in any compartment, the requirement of electroneutrality leads to a strong relationship between charged moieties. This relationship is derived in the form of a general equation stating charge balance, making it possible to calculate [H+] and pH based on all other charged moieties. Therefore, to validate this construct we investigated a large number of blood samples from intensive care patients, where both data and pathology is plentiful, by comparing the measured pH to the modeled pH. We were able to predict both the mean pattern and the individual fluctuation in pH based on all other measured charges with a correlation of approximately 90% in individual patient series. However, there was a shift in pH so that fitted pH in general is overestimated (95% confidence interval -0.072–0.210) and we examine some explanations for this shift. Having confirmed the relationship between charged species we then examine some of the classical and recent literature concerning the importance of charge balance. We conclude that focusing on the charges which are predictable such as strong ions and total concentrations of weak acids leads to new insights with important implications for medicine and physiology. Importantly this construct should pave the way for quantitative acid-base models looking into the underlying mechanisms of disorders rather than just classifying them.
机译:对酸碱调节的了解通常被简化为根据动脉血样将临床状态分类为各种疾病。通过测量酸的产生和消除来定量解释疾病的早期雄心还没有成为标准的临床实践。回到经典的物理化学,我们建议在任何隔间中,电中性的要求导致带电部分之间的牢固关系。该关系以表示电荷平衡的一般公式的形式导出,从而可以基于所有其他带电部分计算[H + ]和pH。因此,为了验证该构建体,我们通过将测得的pH值与建模的pH值进行比较,研究了来自重症监护患者的大量血液样本,这些患者的数据和病理学资料都很丰富。我们能够根据所有其他测得的电荷预测平均模式和pH的个体波动,在各个患者系列中相关性约为90%。但是,pH值发生了变化,因此通常会高估拟合的pH值(95%置信区间-0.072–0.210),我们研究了对此变化的一些解释。在确认带电物种之间的关系之后,我们将考察一些有关电荷平衡重要性的经典文献和最新文献。我们得出的结论是,集中于可预测的电荷,例如强离子和弱酸的总浓度,将导致新的见解,对医学和生理学具有重要意义。重要的是,这种构建方法应该为定量的酸碱模型铺平道路,以研究疾病的潜在机制,而不仅仅是对其进行分类。

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    Troels Ring; John A. Kellum;

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  • 年(卷),期 -1(11),9
  • 年度 -1
  • 页码 e0162872
  • 总页数 21
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