Overcoming safety challenges in CO therapy – Extracorporeal CO delivery under precise feedback control of systemic carboxyhemoglobin levels
Overcoming safety challenges in CO therapy – Extracorporeal CO delivery under precise feedback control of systemic carboxyhemoglobin levels
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DOI：
10.1016/j.jconrel.2018.04.017
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发表时间：
2018-06
影响因子：
10.8
通讯作者：
J. Wollborn;Cornelius Hermann;U. Goebel;B. Merget;C. Wunder;S. Maier;T. Schäfer;Dominik Heuler;K. Müller‐Buschbaum;H. Buerkle;L. Meinel;M. Schick;C. Steiger
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作者：
J. Wollborn;Cornelius Hermann;U. Goebel;B. Merget;C. Wunder;S. Maier;T. Schäfer;Dominik Heuler;K. Müller‐Buschbaum;H. Buerkle;L. Meinel;M. Schick;C. Steiger
一氧化碳(CO)已在多种炎症条件下显示出治疗潜力，包括器官移植或脓毒症等重症监护应用。然而，将这些发现转化为未来疗法的方法受到了多重障碍的挑战，包括与系统性一氧化碳输送相关的处理和毒性问题。在这里，我们描述了一种膜控制的体外一氧化碳释放系统(ECCORS)，该系统易于实施到体外膜氧合(ECMO)装置中，该装置正被用于治疗各种重症监护应用中的心脏和呼吸系统疾病。在猪静脉-动脉ECMO模型上研究了ECCORS的功能。通过根据全身碳氧血红蛋白水平精确控制一氧化碳的产生和释放，该系统允许立即启动治疗性一氧化碳水平，同时防止一氧化碳中毒。通过监测呼出的一氧化碳水平以及脉搏血氧饱和度，实时分析全身碳氧血红蛋白水平，从而实现对ECCORS内一氧化碳生成的独立和自动反馈控制。基于机器学习的数学建模被用来提高这种方法的预测能力，为未来高精度的系统性CO交付概念奠定了基础。
Carbon monoxide (CO) has demonstrated therapeutic potential in multiple inflammatory conditions including intensive care applications such as organ transplantation or sepsis. Approaches to translate these findings into future therapies, however, have been challenged by multiple hurdles including handling and toxicity issues associated with systemic CO delivery. Here, we describe a membrane-controlled Extracorporeal Carbon Monoxide Release System (ECCORS) for easy implementation into Extracorporeal Membrane Oxygenation (ECMO) setups, which are being used to treat cardiac and respiratory diseases in various intensive care applications. Functionalities of the ECCORS were investigated in a pig model of veno-arterial ECMO. By precisely controlling CO generation and delivery as a function of systemic carboxyhemoglobin levels, the system allows for an immediate onset of therapeutic CO-levels while preventing CO-toxicity. Systemic carboxyhemoglobin levels were profiled in real-time by monitoring exhaled CO levels as well as by pulse oximetry, enabling self-contained and automatic feedback control of CO generation within ECCORS. Machine learning based mathematical modeling was performed to increase the predictive power of this approach, laying foundation for high precision systemic CO delivery concepts of tomorrow.